Dissertations / Theses on the topic 'Single object'
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Noé, Estelle. "3D layered articulated object from a single 2D drawing." Thesis, KTH, Medieteknik och interaktionsdesign, MID, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-216943.
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Modeling articulated objects made of rigid layered parts used to populate 3D scenes in video games or movie production is a complex and time-consuming task for digital artists. This work proposes a sketch-based approach to efficiently model 3D layered articulated objects, such as animals with rigid shells and armors, in annotating a single 2D photo manually, and eventually fabricate it from automatically computed 2D patterns. In considering symmetrical objects seen under a 3/4 view, and an- notating salient features such as extremities of the rigid articulated parts as a mix of circular and Bézier curve, this approach is able to retrieve depth information, hidden parts, and rotation-articulated structure. The resulting shape consists of a set of quadrangulated polygons that may be flattened in 2D. Details such as ears, tails, and legs were further models using dedicated annotations. The accuracy of the reconstruction has been validated on synthetic cylindrical examples, and its ro- bustness in reconstructing a 3D model of armor, armadillo, and shrimp. The latter was finally fabricated using paper.Att modellera artikulerade objekt gjorda av styva delar lagda i lager som används till att fylla 3D-scener i datorspel och filmskapande är en komplex och tidsödande uppgift för digitala konstnärer. Den här undersökningen föreslår ett skiss-baserat tillvägagångssätt att effektivt modellera artikulerade 3D-objekt lagda i lager, såsom djur med styva skal och rustning, i att annotera ett 2D-foto manuellt, och eventuellt skapa det från automatiskt beräknade 2D-mönster. Hänsyn är tagen till symmetriska objekt sedda under en 3/4 vy, och annotera framträdande egenskapersåsom extremiteter av de styva artikulerade delarna som en blandning avcirkulära och Bézier-kurvor, kan det här tillvägagångssättet hämta information om djup, gömda delar och rotations-artikulerade strukturer. Den slutliga formen består av ett set av fyrsidiga polygoner som kan bli tillplattade i 2D. Detaljer såsom öron, svansar och ben där framtida modeller använder dedikerade annotationer. Noggrannheten av rekonstruktionen har blivit validerad på syntetiska cylindriska exempeloch dess robusthet i att rekonstruera en 3D-modell av en rustning, ett bältdjur och en räka. Den senare skapades slutligen med hjälp av papper.
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Medeghini, Fabio. "Optics and acoustics with a single nano-object : environment effects." Thesis, Lyon, 2018. http://www.theses.fr/2018LYSE1026/document.
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Dans cette thèse, les propriétés d'une nanoparticule unique ont été réglée en modifiant son environnement.Plus spécifiquement, dans la première partie de ce travail, la résonance des plasmons de surface des nanobipyramides d'or individuelles a été étudié expérimentalement dans un milieu sous pression contrôlable et son évolution encadré par modélisations théoriques.Afin d'accéder à l'optique d'une nanoparticule unique tout en générant un environnement sous haute-pression, la combinaison de la spectroscopie par modulation spatial avec la cellule en enclume de diamant a été atteint.Dans la seconde partie de la thèse, les vibrations acoustiques des nanodisques d'or individuels sur a substrat en saphir ont été caractérisé expérimentalement via spectroscopie pump&probe. Une attention particulière a été accordée à leur amortissement en fonction du rapport d'aspect des disques en soulignant la présence des amplifications en factor de qualité.Modélisations numériques ont fourni un aperçu des amplifications observées, montrant que l'hybridations entre modes se produit pour rapport d'aspect spécifiques, potentiellement en atténuant les pertes en énergie acoustique à travers l'interface disque/substratIn this thesis, the properties of a single nanoparticle have been tuned altering its environment. Specifically, in the first part of this work, the surface plasmon resonance of individual gold nanobipyramids has been experimentally studied under a pressure adjustable surrounding and its evolution physically framed thorough theoretical modeling.In order to access to the single nanoparticle optics while generating a hydrostatic high-pressure environment, a challenging combination of the spatial modulation spectroscopy technique with the diamond anvil cell method has been achieved.In the second part of the thesis, the acoustic vibrations of individual gold nanodisks on sapphire substrate has been experimentally characterized via pump&probe spectroscopy. Particular attention has been paid to their damping as a function of the disks aspect-ratio enlightening the presence of quality-factors enhancements.Numeric modeling has provided a physical insight for the observed amplifications, showing that modes hybridizations occur at specific aspect-ratios, potentially reducing the acoustic energy loss towards the interface disk/substrate
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Taha, Hussein Saad. "Extraction of 3D Object Representations from a Single Range Image." Diss., Virginia Tech, 2000. http://hdl.handle.net/10919/37219.
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The main goal of this research is the automatic construction of a computer model of 3D solid objects from a single range image. This research has many real world applications, including robotic environments and the inspection of industry parts. The most common methods for 3D-object extraction are based on stereo reconstruction and structured light analysis. The first approach encounters the difficulty of finding a correspondence of points between two images for the same scene, which involves intensive computations. The latter, on the other hand, has limitations and difficulties in object extraction, namely, inferring information about 3D objects from a 2D image. In addition, research in 3D-object extraction up to this point has lacked a thorough treatment of overlapped (occluded) objects.
This research has resulted in a system that can extract multiple polyhedral objects from a single range image. The system consists of several parts: edge detection, segmentation, initial vertex extraction, occlusion detection, grouping faces into objects, and object representation. The problem is difficult especially when occluded objects are present. The system that has been developed separates occluded objects by combining evidence of several types.
In the edge detection algorithm, noise reduction for range images is treated first by implementing a statistically robust technique based on the least median of squares. Three approaches to edge detection are presented. One that detects change in gradient orientation is a novel approach, which is implemented in the algorithm due to its superior performance, and the other two are extensions of work by other researchers. In general, the performance of these edge detection methods is considerably better than many others in the domain of range image segmentation.
A hybrid approach (region-edge based) is introduced to achieve a robust solution for a single range image segmentation. The segmentation process depends on collaborating edge and region techniques where they give complementary information about the scene. Region boundaries are improved using iterative refinement.
A novel approach for initial vertex extraction is presented to find the vertices of the polyhedral objects. The 3D vertex locations for the objects are obtained through an analysis of two-dimensional (2D) region shape and corner proximity, and the vertices of the polyhedra are extracted from the individual faces.
There are two major approaches for dealing with occlusion. The first is an automatic identification of layers of 3D solid objects within a single range image. In this novel approach, a histogram of the distance values from a given range image is clustered into separate modes. Ideally, each mode of the histogram will be associated with one or more surfaces having approximately the same distance from the sensor. This approach works well when the objects are lying at different distances from the sensor, but when two or more objects are overlapped and lying at the same distance from the sensor, this approach has difficulty in detecting occlusion.
The second approach for occlusion detection is considered the major contribution of this work. It detects occlusion of 3D solid objects from a single range image using multiple sources of evidence. This technique is based on detecting occlusion that may be present between each pair of adjacent faces associated with the estimated vertices of the 3D objects. This approach is not based on vertex and line labeling as other approaches are; it utilizes the topology and geometrical information of the 3D objects.
After occlusion detection, faces are grouped into objects according to their adjacency relations and the absence or presence of occlusion between them. The initial vertex estimates are improved significantly through a global optimization procedure. Finally, models of the 3D objects are represented using the boundary representation technique that makes use of the region adjacency graph (RAG) paradigm.
The experimental results of this research were obtained using real range images obtained from the CESAR lab at Oak Ridge National Laboratory. These images were obtained using a Perceptron laser range finder. These images contain single and multiple polyhedral objects, and they have a size of 512x512 pixels and a quantization of 12 bits per pixel.
A quantitative evaluation of the construction algorithms is given. Part of this evaluation depends on the comparison between the results of the proposed segmentation technique and the ground truth database for these range images. The other part is to compare the results of the implemented algorithms with the results of other researchers, and it is found that the system developed here exhibits better performance in terms of the accuracy of the boundaries for the regions of the segmented images. A subjective comparison of the new edge detection methods with some traditional approaches is also provided for the set of range images. An evaluation of the new approach to occlusion detection is also presented.
A recommendation for future work is to extend this system to involve images contain objects with curved surfaces. With some modifications to the multiple evidence-based approach of occlusion detection, the curved objects could be addressed. In addition, the model could be updated to include representation of the hidden surfaces for the 3D objects. This could be achieved by using multiple views for the same scene, or through assumptions such as symmetry to infer the shape of the hidden portion of the objects.Ph. D.
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Iván, Kitti. "Mateřská škola v Moravanech u Brna." Master's thesis, Vysoké učení technické v Brně. Fakulta stavební, 2015. http://www.nusl.cz/ntk/nusl-227815.
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Subject of my master´s thesis is to make project documentation for a new building of kindergarten. The building is single – storey, without basement and its capacity is 60 children divided into 3 classes. As foundation system of the building are used foundation strips. Floor plan of the building is irregular. The building is designed from construction system KM BETA. Building is covered by a flat roof.
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Müllner, Jiří. "Novostavba mateřské školy." Master's thesis, Vysoké učení technické v Brně. Fakulta stavební, 2017. http://www.nusl.cz/ntk/nusl-265590.
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The subject of master´s thesis is to make project documentation for a new building of kindergarten in Kuřim. The building is single – storey, without basement and its capacity is 66 children divided into 3 classes. As foundation system of the building are used foundation strips. Floor plan of the building is irregular. The building is designed from construction system Porotherm. Building is covered by a green roof.
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Selim, Hossam Abdelatif Mohamed. "A novel secure autonomous generalized document model using object oriented technique." Thesis, University of Kent, 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.269141.
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CARDONA, YULIETH ALZATE. "OBJECT-BASED MODELING OF TURBIDITE LOBES USING SINGLE-VALUED B-SPLINES." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2016. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=29377@1.
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PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIROCOORDENAÇÃO DE APERFEIÇOAMENTO DO PESSOAL DE ENSINO SUPERIOR
CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO
PROGRAMA DE SUPORTE À PÓS-GRADUAÇÃO DE INSTS. DE ENSINO
PROGRAMA DE EXCELENCIA ACADEMICA
As correntes de turbidez são fluxos gravitacionais que têm uma densidade mais elevada do que o seu entorno, sendo caracterizadas por terem uma aparência turbulenta e por moverem-se com uma alta velocidade, realizando um processo de transferência de sedimentos. O problema abordado nesta tese é a modelagem de depósitos turbidíticos baseada em um modelo deposicional com três lobos turbidíticos. A principal contribuição foi desenvolver um modelo baseado em objectos usando B-Splines univalorados para simular reservatórios de turbiditos em um grade cartesiana regular.
Turbidity currents are gravitational flows that have higher density than its surroundings, and they are characterized by having a turbulent appearance and by moving at high speed carrying out a transfer process sediment. The problem addressed in this thesis is the modelling of turbidities deposits. It will be taken based on a depositional model that contains three turbidities lobes. Our contribution is to develop a object-based model using Single-valued B-Spline to simulate turbidities reservoirs in a regular Cartesian grid.
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Singh, Mahendra, Stuart McNamee, Rick Navarro, Amy Fleishans, Louie Garcia, and Allen Khosrowabadi. "IMPROVING PERFORMANCE OF SINGLE OBJECT TRACKING RADAR WITH INTEGRATED GPS/INS." International Foundation for Telemetering, 2000. http://hdl.handle.net/10150/608266.
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International Telemetering Conference Proceedings / October 23-26, 2000 / Town & Country Hotel and Conference Center, San Diego, CaliforniaA novel approach combines GPS receiver technology with micro-electromechanical inertial sensors to improve performance of single object tracking radar. The approach enhances range safety by integrating an airborne Global Positioning System/Inertial Movement Unit (GPS/IMU) with a C-band transponder to downlink time-space-position information (TSPI) via FPS-16 instrumentation radar. This improves current telemetry links and the Range Application Joint Program Office (RAJPO) data link for downlinking TSPI because of the inherent long-range advantage of the radar. The goal of the project is to provide distance independent accuracy, and to demonstrate continuous 15-meter or better position accuracy over the entire flight envelope out to slant ranges up to 1,000 Km with at least 50 updates per second. This improves safety coverage for the wide area flight testing. It provides risk reduction for the Air Force Flight Test Center (AFFTC), Edwards Air Force Base, California and other ranges planning TSPI system upgrades.
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Lee, Heewon. "Estimating True Object Color from a Single Image and Multiple Images." The Ohio State University, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=osu1357230807.
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Zhang, Shujun. "Model-based 3D object perception from single monochromatic images of unknown environments." Thesis, University of Reading, 1992. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.315501.
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Jansson, Martin, and Simon Petersson. "Object detection and single-board computers : En förstudie gjord på Saab AB." Thesis, Linnéuniversitetet, Institutionen för datavetenskap och medieteknik (DM), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-75981.
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Saab använder sig i nuläget av ett utdaterat system för att utföra tester av deras produkter. Systemet filmar ur olika vinklar och sammanfogar videoströmmarna till en slutgiltig video, där de sedan kan analysera resultatet av produkten. Enkortsdatorer är något som på senare år har blivit mer och mer populärt, Saab vill därför undersöka om det går att ersätta det äldre systemet med enkortsdatorer och kameror.Det ska undersökas om enkortsdatorn BeagleBoard klarar av att köra objektidentifiering samtidigt som den filmar och utför operationer som videosynkning, videokodning samt sparar den synkade filmen.Undersökningen visade att BeagleBoardens processor inte är tillräckligt kraftfull för att klara av objektidentifieringen utan hårdvarustöd. Istället behöver det utföras av en dator som bearbetar filmen i efterhand och plockar ut objekt. Det har förslagits en bättre metod för att göra objektidentifieringen smartare och lärande som kommer fungera bättre i Saabs fall.Saab is currently using an old and complex system to perform tests of their products. The system is based on filming from different angles which will be merged to one film from which Saab can analyze the results of their products. Single-board computers is something that have become increasingly popular in the recent years, therefore, we are to investigate whether it is possible or not to replace the older systems with SBCs and cameras.We will also investigate whether the BeagleBoard is capable of detecting objects while filming, synchronizing, encoding and saving the video for later use.The result showed that the processor isn’t powerful enough to handle object identification without full hardware support. Instead, it needs to be performed afterwards by a computer which will identify objects in the video. A better method has been proposed to make object identification smarter and learning, which will work better in Saab’s case and their future work.
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Donnelly, Kieran. "Development of a test suite for single object tracking algorithms in video." Master's thesis, Faculty of Science, 2021. http://hdl.handle.net/11427/33645.
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Flying Camera Solutions (FlyCam), within Sony Lund's startup accelerator, intends to provide drone videography to paying customers in ski resorts: a customer should be able to go about their activity as usual while a drone films them. Visual object tracking, enabling the drone to track the customer throughout the activity, is a primary obstacle in creating a viable autonomous videography service. FlyCam needs an object tracking algorithm which is accurate, robust, real-time, and requiring minimal computational overhead. We propose two innovations to aid in the selection of an appropriate tracking algorithm. Firstly, a video annotation algorithm, making use of an object detector to record the position and type of object in each frame of a video clip. Secondly, an algorithm designed to evaluate the performance of any given object tracker based on a set of performance metrics. These metrics include, among others, measures of positional accuracy, frame rate, and false positive rate. For the video annotation algorithm we implemented the state-of-the-art Mask R-CNN object detector, which achieved an average frame rate of 1.5 fps annotating video clips in up to 4K resolution. Another algorithm then played back the annotated clips to the user such that incorrect object detections could be rooted out or rectified. With little relevant annotated video available, the annotation algorithm proved useful in preparing a suite of 18 clips to be evaluated. Ten performance metrics were adapted from multi-object to single-object tracking. Nine tracking algorithms were then run on each of the 18 test video clips at varying resolutions to produce 375 tracking observations for analysis. The evaluation results revealed the optimal tracking algorithm to be Re3: a recurrent-convolutional neural network tracker which runs at respectable speeds on a consumer laptop. This is a promising result; with enough annotated data, neural networks can be retrained to improve performance. Within just a few months of operation, FlyCam could amass enough specific video data to significantly improve the neural network-based tracker.
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Barkman, Richard Dan William. "Object Tracking Achieved by Implementing Predictive Methods with Static Object Detectors Trained on the Single Shot Detector Inception V2 Network." Thesis, Karlstads universitet, Fakulteten för hälsa, natur- och teknikvetenskap (from 2013), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kau:diva-73313.
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In this work, the possibility of realising object tracking by implementing predictive methods with static object detectors is explored. The static object detectors are obtained as models trained on a machine learning algorithm, or in other words, a deep neural network. Specifically, it is the single shot detector inception v2 network that will be used to train such models. Predictive methods will be incorporated to the end of improving the obtained models’ precision, i.e. their performance with respect to accuracy. Namely, Lagrangian mechanics will be employed to derived equations of motion for three different scenarios in which the object is to be tracked. These equations of motion will be implemented as predictive methods by discretising and combining them with four different iterative formulae. In ch. 1, the fundamentals of supervised machine learning, neural networks, convolutional neural networks as well as the workings of the single shot detector algorithm, approaches to hyperparameter optimisation and other relevant theory is established. This includes derivations of the relevant equations of motion and the iterative formulae with which they were implemented. In ch. 2, the experimental set-up that was utilised during data collection, and the manner by which the acquired data was used to produce training, validation and test datasets is described. This is followed by a description of how the approach of random search was used to train 64 models on 300×300 datasets, and 32 models on 512×512 datasets. Consecutively, these models are evaluated based on their performance with respect to camera-to-object distance and object velocity. In ch. 3, the trained models were verified to possess multi-scale detection capabilities, as is characteristic of models trained on the single shot detector network. While the former is found to be true irrespective of the resolution-setting of the dataset that the model has been trained on, it is found that the performance with respect to varying object velocity is significantly more consistent for the lower resolution models as they operate at a higher detection rate. Ch. 3 continues with that the implemented predictive methods are evaluated. This is done by comparing the resulting deviations when they are let to predict the missing data points from a collected detection pattern, with varying sampling percentages. It is found that the best predictive methods are those that make use of the least amount of previous data points. This followed from that the data upon which evaluations were made contained an unreasonable amount of noise, considering that the iterative formulae implemented do not take noise into account. Moreover, the lower resolution models were found to benefit more than those trained on the higher resolution datasets because of the higher detection frequency they can employ. In ch. 4, it is argued that the concept of combining predictive methods with static object detectors to the end of obtaining an object tracker is promising. Moreover, the models obtained on the single shot detector network are concluded to be good candidates for such applications. However, the predictive methods studied in this thesis should be replaced with some method that can account for noise, or be extended to be able to account for it. A profound finding is that the single shot detector inception v2 models trained on a low-resolution dataset were found to outperform those trained on a high-resolution dataset in certain regards due to the higher detection rate possible on lower resolution frames. Namely, in performance with respect to object velocity and in that predictive methods performed better on the low-resolution models.I detta arbete undersöks möjligheten att åstadkomma objektefterföljning genom att implementera prediktiva metoder med statiska objektdetektorer. De statiska objektdetektorerna erhålls som modeller tränade på en maskininlärnings-algoritm, det vill säga djupa neurala nätverk. Specifikt så är det en modifierad version av entagningsdetektor-nätverket, så kallat entagningsdetektor inception v2 nätverket, som används för att träna modellerna. Prediktiva metoder inkorporeras sedan för att förbättra modellernas förmåga att kunna finna ett eftersökt objekt. Nämligen används Lagrangiansk mekanik för härleda rörelseekvationer för vissa scenarion i vilka objektet är tänkt att efterföljas. Rörelseekvationerna implementeras genom att låta diskretisera dem och därefter kombinera dem med fyra olika iterationsformler. I kap. 2 behandlas grundläggande teori för övervakad maskininlärning, neurala nätverk, faltande neurala nätverk men också de grundläggande principer för entagningsdetektor-nätverket, närmanden till hyperparameter-optimering och övrig relevant teori. Detta inkluderar härledningar av rörelseekvationerna och de iterationsformler som de skall kombineras med. I kap. 3 så redogörs för den experimentella uppställning som användes vid datainsamling samt hur denna data användes för att producera olika data set. Därefter följer en skildring av hur random search kunde användas för att träna 64 modeller på data av upplösning 300×300 och 32 modeller på data av upplösning 512×512. Vidare utvärderades modellerna med avseende på deras prestanda för varierande kamera-till-objekt avstånd och objekthastighet. I kap. 4 så verifieras det att modellerna har en förmåga att detektera på flera skalor, vilket är ett karaktäristiskt drag för modeller tränade på entagninsdetektor-nätverk. Medan detta gällde för de tränade modellerna oavsett vilken upplösning av data de blivit tränade på, så fanns detekteringsprestandan med avseende på objekthastighet vara betydligt mer konsekvent för modellerna som tränats på data av lägre upplösning. Detta resulterade av att dessa modeller kan arbeta med en högre detekteringsfrekvens. Kap. 4 fortsätter med att de prediktiva metoderna utvärderas, vilket de kunde göras genom att jämföra den resulterande avvikelsen de respektive metoderna innebar då de läts arbeta på ett samplat detektionsmönster, sparat från då en tränad modell körts. I och med denna utvärdering så testades modellerna för olika samplingsgrader. Det visade sig att de bästa iterationsformlerna var de som byggde på färre tidigare datapunkter. Anledningen för detta är att den insamlade data, som testerna utfördes på, innehöll en avsevärd mängd brus. Med tanke på att de implementerade iterationsformlerna inte tar hänsyn till brus, så fick detta avgörande konsekvenser. Det fanns även att alla prediktiva metoder förbättrade objektdetekteringsförmågan till en högre utsträckning för modellerna som var tränade på data av lägre upplösning, vilket följer från att de kan arbeta med en högre detekteringsfrekvens. I kap. 5, argumenteras det, bland annat, för att konceptet att kombinera prediktiva metoder med statiska objektdetektorer för att åstadkomma objektefterföljning är lovande. Det slutleds även att modeller som erhålls från entagningsdetektor-nätverket är lovande kandidater för detta applikationsområde, till följd av deras höga detekteringsfrekvenser och förmåga att kunna detektera på flera skalor. Metoderna som användes för att förutsäga det efterföljda föremålets position fanns vara odugliga på grund av deras oförmåga att kunna hantera brus. Det slutleddes därmed att dessa antingen bör utökas till att kunna hantera brus eller ersättas av lämpligare metoder. Den mest väsentliga slutsats detta arbete presenterar är att lågupplösta entagninsdetektormodeller utgör bättre kandidater än de tränade på data av högre upplösning till följd av den ökade detekteringsfrekvens de erbjuder.
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Yang, Tao. "visual tracking and object motion prediction for intelligent vehicles." Thesis, Bourgogne Franche-Comté, 2019. http://www.theses.fr/2019UBFCA005.
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Le suivi d’objets et la prédiction de mouvement sont des aspects importants pour les véhicules autonomes. Tout d'abord, nous avons développé une méthode de suivi mono-objet en utilisant le compressive tracking, afin de corriger le suivi à base de flux optique et d’arriver ainsi à un compromis entre performance et vitesse de traitement. Compte tenu de l'efficacité de l'extraction de caractéristiques comprimées (compressive features), nous avons appliqué cette méthode de suivi au cas multi-objets pour améliorer les performances sans trop ralentir la vitesse de traitement. Deuxièmement, nous avons amélioré la méthode de suivi mono-objet basée sur DCF en utilisant des caractéristiques provenant d’un CNN multicouches, une analyse de fiabilité spatiale (via un masque d'objet) ainsi qu’une stratégie conditionnelle de mise à jour de modèle. Ensuite, nous avons appliqué la méthode améliorée au cas du suivi multi-objets. Les VGGNet-19 et DCFNet pré-entraînés sont testés respectivement en tant qu’extracteurs de caractéristiques. Le modèle discriminant réalisé par DCF est pris en compte dans l’étape d'association des données. Troisièmement, deux modèles LSTM (seq2seq et seq2dense) pour la prédiction de mouvement des véhicules et piétons dans le système de référence de la caméra sont proposés. En se basant sur des données visuelles et un nuage de points 3D (LiDAR), un système de suivi multi-objets basé sur un filtre de Kalman avec un détecteur 3D sont utilisés pour générer les trajectoires des objets à tester. Les modèles proposées et le modèle de régression polynomiale, considéré comme méthode de référence, sont comparés et évaluésObject tracking and motion prediction are important for autonomous vehicles and can be applied in many other fields. First, we design a single object tracker using compressive tracking to correct the optical flow tracking in order to achieve a balance between performance and processing speed. Considering the efficiency of compressive feature extraction, we apply this tracker to multi-object tracking to improve the performance without slowing down too much speed. Second, we improve the DCF based single object tracker by introducing multi-layer CNN features, spatial reliability analysis (through a foreground mask) and conditionally model updating strategy. Then, we apply the DCF based CNN tracker to multi-object tracking. The pre-trained VGGNet-19 and DCFNet are tested as feature extractors respectively. The discriminative model achieved by DCF is considered for data association. Third, two proposed LSTM models (seq2seq and seq2dense) for motion prediction of vehicles and pedestrians in the camera coordinate are proposed. Based on visual data and 3D points cloud (LiDAR), a Kalman filter based multi-object tracking system with a 3D detector are used to generate the object trajectories for testing. The proposed models, and polynomial regression model, considered as baseline, are compared for evaluation
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Rycková, Silvie. "Letiště Zábřeh." Master's thesis, Vysoké učení technické v Brně. Fakulta stavební, 2015. http://www.nusl.cz/ntk/nusl-227317.
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Subject of my master´s thesis is to make a project documentation for a new building of airport. The building is three–storeys, without basement. Foundation strips are used as a foundation system of the building. Floor plan of the building is in a rectangle shape. The building is designed from YTONG construction system. The building is covered by a flat roof.
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Taurone, Francesco. "3D Object Recognition from a Single Image via Patch Detection by a Deep CNN." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2019. http://amslaurea.unibo.it/18669/.
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This thesis describes the development of a new technique for recognizing the 3D pose of an object via a single image. The whole project is based on a CNN for recognizing patches on the object, that we use for estimating the pose given an a priori model.
The positions of the patches, together with the knowledge of their coordinates in the model, make the estimation of the pose possible through a solution of a PnP problem. The CNN chosen for this project is Yolo.
In order to build the training dataset for the network, a new approach is used. Instead of labeling each individual training image as for the standard supervised learning, the initial coordinates of the patches are propagated on all the other images making use of the pose of the camera for all the pictures.
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Horáček, Radek. "Nursery school." Master's thesis, Vysoké učení technické v Brně. Fakulta stavební, 2014. http://www.nusl.cz/ntk/nusl-226657.
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Subject of my master’s thesis is to make project documentation for new building of nursery school. The building is single-storey, without basement and its capacity is 60 children divided into 4 classes. As foundation system of the building are used foundation strips. Floor plan of the building is irregular, main buildings orientation is to the south. Building is covered partially by a flat roof and partially by a truss roof.
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Ghorpade, Vijaya Kumar. "3D Semantic SLAM of Indoor Environment with Single Depth Sensor." Thesis, Université Clermont Auvergne (2017-2020), 2017. http://www.theses.fr/2017CLFAC085/document.
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Pour agir de manière autonome et intelligente dans un environnement, un robot mobile doit disposer de cartes. Une carte contient les informations spatiales sur l’environnement. La géométrie 3D ainsi connue par le robot est utilisée non seulement pour éviter la collision avec des obstacles, mais aussi pour se localiser et pour planifier des déplacements. Les robots de prochaine génération ont besoin de davantage de capacités que de simples cartographies et d’une localisation pour coexister avec nous. La quintessence du robot humanoïde de service devra disposer de la capacité de voir comme les humains, de reconnaître, classer, interpréter la scène et exécuter les tâches de manière quasi-anthropomorphique. Par conséquent, augmenter les caractéristiques des cartes du robot à l’aide d’attributs sémiologiques à la façon des humains, afin de préciser les types de pièces, d’objets et leur aménagement spatial, est considéré comme un plus pour la robotique d’industrie et de services à venir. Une carte sémantique enrichit une carte générale avec les informations sur les entités, les fonctionnalités ou les événements qui sont situés dans l’espace. Quelques approches ont été proposées pour résoudre le problème de la cartographie sémantique en exploitant des scanners lasers ou des capteurs de temps de vol RGB-D, mais ce sujet est encore dans sa phase naissante. Dans cette thèse, une tentative de reconstruction sémantisée d’environnement d’intérieur en utilisant une caméra temps de vol qui ne délivre que des informations de profondeur est proposée. Les caméras temps de vol ont modifié le domaine de l’imagerie tridimensionnelle discrète. Elles ont dépassé les scanners traditionnels en termes de rapidité d’acquisition des données, de simplicité fonctionnement et de prix. Ces capteurs de profondeur sont destinés à occuper plus d’importance dans les futures applications robotiques. Après un bref aperçu des approches les plus récentes pour résoudre le sujet de la cartographie sémantique, en particulier en environnement intérieur. Ensuite, la calibration de la caméra a été étudiée ainsi que la nature de ses bruits. La suppression du bruit dans les données issues du capteur est menée. L’acquisition d’une collection d’images de points 3D en environnement intérieur a été réalisée. La séquence d’images ainsi acquise a alimenté un algorithme de SLAM pour reconstruire l’environnement visité. La performance du système SLAM est évaluée à partir des poses estimées en utilisant une nouvelle métrique qui est basée sur la prise en compte du contexte. L’extraction des surfaces planes est réalisée sur la carte reconstruite à partir des nuages de points en utilisant la transformation de Hough. Une interprétation sémantique de l’environnement reconstruit est réalisée. L’annotation de la scène avec informations sémantiques se déroule sur deux niveaux : l’un effectue la détection de grandes surfaces planes et procède ensuite en les classant en tant que porte, mur ou plafond; l’autre niveau de sémantisation opère au niveau des objets et traite de la reconnaissance des objets dans une scène donnée. A partir de l’élaboration d’une signature de forme invariante à la pose et en passant par une phase d’apprentissage exploitant cette signature, une interprétation de la scène contenant des objets connus et inconnus, en présence ou non d’occultations, est obtenue. Les jeux de données ont été mis à la disposition du public de la recherche universitaireIntelligent autonomous actions in an ordinary environment by a mobile robot require maps. A map holds the spatial information about the environment and gives the 3D geometry of the surrounding of the robot to not only avoid collision with complex obstacles, but also selflocalization and for task planning. However, in the future, service and personal robots will prevail and need arises for the robot to interact with the environment in addition to localize and navigate. This interaction demands the next generation robots to understand, interpret its environment and perform tasks in human-centric form. A simple map of the environment is far from being sufficient for the robots to co-exist and assist humans in the future. Human beings effortlessly make map and interact with environment, and it is trivial task for them. However, for robots these frivolous tasks are complex conundrums. Layering the semantic information on regular geometric maps is the leap that helps an ordinary mobile robot to be a more intelligent autonomous system. A semantic map augments a general map with the information about entities, i.e., objects, functionalities, or events, that are located in the space. The inclusion of semantics in the map enhances the robot’s spatial knowledge representation and improves its performance in managing complex tasks and human interaction. Many approaches have been proposed to address the semantic SLAM problem with laser scanners and RGB-D time-of-flight sensors, but it is still in its nascent phase. In this thesis, an endeavour to solve semantic SLAM using one of the time-of-flight sensors which gives only depth information is proposed. Time-of-flight cameras have dramatically changed the field of range imaging, and surpassed the traditional scanners in terms of rapid acquisition of data, simplicity and price. And it is believed that these depth sensors will be ubiquitous in future robotic applications. In this thesis, an endeavour to solve semantic SLAM using one of the time-of-flight sensors which gives only depth information is proposed. Starting with a brief motivation in the first chapter for semantic stance in normal maps, the state-of-the-art methods are discussed in the second chapter. Before using the camera for data acquisition, the noise characteristics of it has been studied meticulously, and properly calibrated. The novel noise filtering algorithm developed in the process, helps to get clean data for better scan matching and SLAM. The quality of the SLAM process is evaluated using a context-based similarity score metric, which has been specifically designed for the type of acquisition parameters and the data which have been used. Abstracting semantic layer on the reconstructed point cloud from SLAM has been done in two stages. In large-scale higher-level semantic interpretation, the prominent surfaces in the indoor environment are extracted and recognized, they include surfaces like walls, door, ceiling, clutter. However, in indoor single scene object-level semantic interpretation, a single 2.5D scene from the camera is parsed and the objects, surfaces are recognized. The object recognition is achieved using a novel shape signature based on probability distribution of 3D keypoints that are most stable and repeatable. The classification of prominent surfaces and single scene semantic interpretation is done using supervised machine learning and deep learning systems. To this end, the object dataset and SLAM data are also made publicly available for academic research
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Glynn, Patrick Joseph, and n/a. "Collision Avoidance Systems for Mine Haul Trucks and Unambiguous Dynamic Real Time Single Object Detection." Griffith University. Griffith Business School, 2005. http://www4.gu.edu.au:8080/adt-root/public/adt-QGU20060809.163025.
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A suite of new collision avoidance systems (CAS) is presented for use in heavy vehicles whose structure and size necessarily impede driver visibility is introduced. The main goal of the project is to determine the appropriate use of each of the commercially available technologies and, where possible, produce a low cost variant suitable for use in proximity detection on large mining industry haul trucks. CAS variants produced were subjected to a field demonstration and, linked to the output from the earlier CAS 1 project, (a production high-definition in-cabin video monitor and r/f tagging system). The CAS 2 system used low cost Doppler continuous wave radar antennae coupled to the CAS 1 monitor to indicate the presence of an object moving at any speed above 3 Km/h relative to the antennae. The novelty of the CAS 3 system lies in the design of 3 interconnected, modules. The modules are 8 radar antennae (as used in CAS 2) modules located on the truck, software to interface with the end user (i.e. the drivers of the trucks) and a display unit. Modularisation enables the components to be independently tested, evaluated and replaced when in use. The radar antennae modules and the system as a whole are described together with the empirical tests conducted and results obtained. The tests, drawing on Monte-Carlo simulation techniques, demonstrate both the 'correctness' of the implementations and the effectiveness of the system. The results of the testing of the final prototype unit were highly successful both as a computer simulation level and in practical tests on light vehicles. A number of points, (as a consequence of the field test), are reviewed and their application to future projects discussed.
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Glynn, Patrick Joseph. "Collision Avoidance Systems for Mine Haul Trucks and Unambiguous Dynamic Real Time Single Object Detection." Thesis, Griffith University, 2005. http://hdl.handle.net/10072/365488.
Full textAbstract:
A suite of new collision avoidance systems (CAS) is presented for use in heavy vehicles whose structure and size necessarily impede driver visibility is introduced. The main goal of the project is to determine the appropriate use of each of the commercially available technologies and, where possible, produce a low cost variant suitable for use in proximity detection on large mining industry haul trucks. CAS variants produced were subjected to a field demonstration and, linked to the output from the earlier CAS 1 project, (a production high-definition in-cabin video monitor and r/f tagging system). The CAS 2 system used low cost Doppler continuous wave radar antennae coupled to the CAS 1 monitor to indicate the presence of an object moving at any speed above 3 Km/h relative to the antennae. The novelty of the CAS 3 system lies in the design of 3 interconnected, modules. The modules are 8 radar antennae (as used in CAS 2) modules located on the truck, software to interface with the end user (i.e. the drivers of the trucks) and a display unit. Modularisation enables the components to be independently tested, evaluated and replaced when in use. The radar antennae modules and the system as a whole are described together with the empirical tests conducted and results obtained. The tests, drawing on Monte-Carlo simulation techniques, demonstrate both the 'correctness' of the implementations and the effectiveness of the system. The results of the testing of the final prototype unit were highly successful both as a computer simulation level and in practical tests on light vehicles. A number of points, (as a consequence of the field test), are reviewed and their application to future projects discussed.Thesis (PhD Doctorate)
Doctor of Philosophy (PhD)
Griffith Business School
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Tu, Guoyun. "Image Captioning On General Data And Fashion Data : An Attribute-Image-Combined Attention-Based Network for Image Captioning on Mutli-Object Images and Single-Object Images." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-282925.
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Image captioning is a crucial field across computer vision and natural language processing. It could be widely applied to high-volume web images, such as conveying image content to visually impaired users. Many methods are adopted in this area such as attention-based methods, semantic-concept based models. These achieve excellent performance on general image datasets such as the MS COCO dataset. However, it is still left unexplored on single-object images.In this paper, we propose a new attribute-information-combined attention- based network (AIC-AB Net). At each time step, attribute information is added as a supplementary of visual information. For sequential word generation, spatial attention determines specific regions of images to pass the decoder. The sentinel gate decides whether to attend to the image or to the visual sentinel (what the decoder already knows, including the attribute information). Text attribute information is synchronously fed in to help image recognition and reduce uncertainty.We build a new fashion dataset consisting of fashion images to establish a benchmark for single-object images. This fashion dataset consists of 144,422 images from 24,649 fashion products, with one description sentence for each image. Our method is tested on the MS COCO dataset and the proposed Fashion dataset. The results show the superior performance of the proposed model on both multi-object images and single-object images. Our AIC-AB net outperforms the state-of-the-art network, Adaptive Attention Network by 0.017, 0.095, and 0.095 (CIDEr Score) on the COCO dataset, Fashion dataset (Bestsellers), and Fashion dataset (all vendors), respectively. The results also reveal the complement of attention architecture and attribute information.Bildtextning är ett avgörande fält för datorsyn och behandling av naturligt språk. Det kan tillämpas i stor utsträckning på högvolyms webbbilder, som att överföra bildinnehåll till synskadade användare. Många metoder antas inom detta område såsom uppmärksamhetsbaserade metoder, semantiska konceptbaserade modeller. Dessa uppnår utmärkt prestanda på allmänna bilddatamängder som MS COCO-dataset. Det lämnas dock fortfarande outforskat på bilder med ett objekt.I denna uppsats föreslår vi ett nytt attribut-information-kombinerat uppmärksamhetsbaserat nätverk (AIC-AB Net). I varje tidsteg läggs attributinformation till som ett komplement till visuell information. För sekventiell ordgenerering bestämmer rumslig uppmärksamhet specifika regioner av bilder som ska passera avkodaren. Sentinelgrinden bestämmer om den ska ta hand om bilden eller den visuella vaktposten (vad avkodaren redan vet, inklusive attributinformation). Text attributinformation matas synkront för att hjälpa bildigenkänning och minska osäkerheten.Vi bygger en ny modedataset bestående av modebilder för att skapa ett riktmärke för bilder med en objekt. Denna modedataset består av 144 422 bilder från 24 649 modeprodukter, med en beskrivningsmening för varje bild. Vår metod testas på MS COCO dataset och den föreslagna Fashion dataset. Resultaten visar den överlägsna prestandan hos den föreslagna modellen på både bilder med flera objekt och enbildsbilder. Vårt AIC-AB-nät överträffar det senaste nätverket Adaptive Attention Network med 0,017, 0,095 och 0,095 (CIDEr Score) i COCO-datasetet, modedataset (bästsäljare) respektive modedatasetet (alla leverantörer). Resultaten avslöjar också komplementet till uppmärksamhetsarkitektur och attributinformation.
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Ozkilic, Sibel. "Performance Improvement Of A 3-d Configuration Reconstruction Algorithm For An Object Using A Single Camera Image." Master's thesis, METU, 2004. http://etd.lib.metu.edu.tr/upload/1095793/index.pdf.
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Performance improvement of a 3-D configuration reconstruction algorithm using a passive secondary target has been focused in this study. In earlier studies, a theoretical development of the 3-D configuration reconstruction algorithm was achieved and it was implemented by a computer program on a system consisting of an optical bench and a digital imaging system. The passive secondary target used was a circle with two internal spots.
In order to use this reconstruction algorithm in autonomous systems, an automatic target recognition algorithm has been developed in this study. Starting from a pre-captured and stored 8-bit gray-level image, the algorithm automatically detects the elliptical image of a circular target and determines its contour in the scene. It was shown that the algorithm can also be used for partially captured elliptical images.
Another improvement achieved in this study is the determination of internal camera parameters of the vision system.
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Fasth, Niklas, and Rasmus Hallblad. "Air Reconnaissance Analysis using Convolutional Neural Network-based Object Detection." Thesis, Mälardalens högskola, Akademin för innovation, design och teknik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-48422.
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The Swedish armed forces use the Single Source Intelligent Cell (SSIC), developed by Saab, for analysis of aerial reconnaissance video and report generation. The analysis can be time-consuming and demanding for a human operator. In the analysis workflow, identifying vehicles is an important part of the work. Artificial Intelligence is widely used for analysis in many industries to aid or replace a human worker. In this paper, the possibility to aid the human operator with air reconnaissance data analysis is investigated, specifically, object detection for finding cars in aerial images. Many state-of-the-art object detection models for vehicle detection in aerial images are based on a Convolutional Neural Network (CNN) architecture. The Faster R-CNN- and SSD-based models are both based on this architecture and are implemented. Comprehensive experiments are conducted using the models on two different datasets, the open Video Verification of Identity (VIVID) dataset and a confidential dataset provided by Saab. The datasets are similar, both consisting of aerial images with vehicles. The initial experiments are conducted to find suitable configurations for the proposed models. Finally, an experiment is conducted to compare the performance of a human operator and a machine. The results from this work prove that object detection can be used to supporting the work of air reconnaissance image analysis regarding inference time. The current performance of the object detectors makes applications, where speed is more important than accuracy, most suitable.
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Abbas, Ahmed Khodair Abbas. "A dynamic planner for object assembly tasks based learning the spatial relationships of its parts from a single demonstration." Thesis, Queensland University of Technology, 2021. https://eprints.qut.edu.au/207935/1/Ahmed%20Khodair%20Abbas_Abbas_Thesis.pdf.
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The main application of collaborative robots is helping workers during assembly tasks.
Most assembly task robots are limited to fixed scenarios that do not require reasoning.
To address the current limitations, this thesis introduces a goal-directed dynamic AI system that enables robots to help workers during assembly tasks. After observing an object being assembled, our AI system can induce a 3D model of the assembled object.
This induced model encodes the spatial relationships between the components of the object and allows a dynamic planner to repair assembly plans when the worker deviate from the initial plan.
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Halstead, Michael A. "Locating people in video surveillance from semantic descriptions." Thesis, Queensland University of Technology, 2017. https://eprints.qut.edu.au/112818/1/Michael_Halstead_Thesis.pdf.
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This PhD research developed new approaches to locate individuals in surveillance footage from a semantically describable target description. Investigations in this programme focused on the use of soft biometrics such as clothing colours and patterns, and height as traits to locate a target subject in video. This facilitated the introduction of techniques able to reduce the impact on human operators in surveillance settings.
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Hunt, Aimee D. "Beyond the Single Story: How Analog Hypertext Facilitates Representation of Multiple Critical Perspectives in an Art Museum Object Study Gallery." VCU Scholars Compass, 2016. http://scholarscompass.vcu.edu/etd/4642.
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This project utilized a form of arts based educational research described as analog hypertext to develop interpretative material representing multiple critical, theoretical, and disciplinary perspectives on objects in a university art museum’s object study gallery. Drawing on scholars’ recommendations for postcolonial interpretation of non-Western art, the project created a web of information, which simultaneously revealed and critiqued the underlying ideologies and power structures shaping the museum’s display in an effort to change existing interpretive practice. The project developed five color-coded thematic self-guided tours—art as commodity, spiritual practice, technology and cultural evolutionism, mortuary rituals, and postcolonial perspectives—presented to the public as an interpretive exhibition invited visitors’ contributions. This paper explores how the analog hypertext functions as both a research tool and a content delivery device for the representation of multiple critical perspectives, fostering interdisciplinary perspectives and visitor meaning-making in the process.
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Smedman, Gustaf, and Timo Kervinen. "Spectrum auctions in Sweden : A theoretical study of spectrum auctions in Sweden." Thesis, Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-48728.
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This paper seeks to find whether the spectrum auctions in Sweden have been conducted efficiently and if there is a de facto model that suits all auctions. The efficiency is conditions that emphasise truthful bidding, price discovery and limits collusive behaviour. The paper compares three different auction models used in Sweden, a beauty contest used in the allocation of 3G spectrums, and the auction model selected for the upcoming 5G spectrum auction. The auction models are as follows: first and second-price sealed-bid auction, SMRA and CCA. We found that beauty contests should not be used in any spectrum allocation as it did not meet the criteria of efficiency outlined in this paper. The first-price sealed-bid auction is not a suitable format for spectrum auctions. According to the theory, it generates equivalent revenues on average as the second-price format, which shows a higher degree of efficient allocation. We found that depending on the blocks sold, both SMRA and CCA can result in somewhat efficient results, but they are not suitable for a single object auction. We found that no de facto auction format is suitable for every spectrum auction to be conducted in the future, but instead that the auction format is dependent on the characteristics of the individual auctions.
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Danielsson, Oscar. "Shape-based Representations and Boosting for Visual Object Class Detection : Models and methods for representaion and detection in single and multiple views." Doctoral thesis, KTH, Datorseende och robotik, CVAP, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-58479.
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Detection of generic visual object classes (i.e. cars, dogs, mugs or people) in images is a task that humans are able to solve with remarkable ease. Unfortunately this has proven a very challenging task for computer vision. Thereason is that different instances of the same class may look very different, i.e. there is a high intra-class variation. There are several causes for intra-class variation; for example (1) the imaging conditions (e.g. lighting and exposure) may change, (2) different objects of the same class typically differ in shape and appearance, (3) the position of the object relative to the camera (i.e. the viewpoint) may change and (4) some objects are articulate and may change pose. In addition the background class, i.e. everything but the target object class, is very large. It is the combination of very high intra-class variation with a large background class that makes generic object class detection difficult. This thesis addresses this challenge within the AdaBoost framework. AdaBoost constructs an ensemble of weak classifiers to solve a given classification task and allows great flexibility in the design of these weak classifiers. This thesis proposes several types of weak classifiers that specifically target some of the causes of high intra-class variation. A multi-local classifier is proposed to capture global shape properties for object classes that lack discriminative local features, projectable classifiers are proposed to handle detection from multiple viewpoints and finally gated classifiers are proposed as a generic way to handle high intra-class variation in combination with a large background class. All proposed weak classifiers are evaluated on standard datasets to allow performance comparison to other related methods.Vi människor kan utan ansträngning känna igen ett stort antal visuella objektklasser (såsom bilar, hundar, koppar eller människor). Tyvärr har det visat sig mycket svårt att programmera en dator att göra samma sak. Anledningen är att olika objekt från samma klass kan ha mycket olika utseende, beroende på att (1) avbildningsförutsättningar (exempelvis ljussättning och exponering) kan förändras, (2) olika objekt från samma klass har ofta mycket olika fysiska egenskaper (såsom färg, form eller material), (3) synvinkeln förändras och (4) rörliga objekt kan inta olika ställningar. Utöver detta är bakgrundsklassen, d.v.s. alla tänkbara bilder som inte föreställer ett objekt från målklassen, mycket stor. Det är kombinationen av hög intraklassvariation och stor bakgrundsklass som gör objektigenkänning till ett svårt problem. Denna utmaning bemöter vi inom ramarna för maskininlärningsmetoden AdaBoost. AdaBoost bygger en kraftfull klassificerare genom att kombinera ett stort antal svaga klassificerare, vars utformning är mycket fri. Denna avhandling behandlar flera olika typer av svaga klassificerare vars målsättning är att hantera några av orsakerna till intraklassvariation. Vi föreslår en multilokal klassificerare för att fånga icke-lokala formegenskaper hos objektklassersom saknar diskriminativa lokala egenskaper. Vi föreslår vidare projicerbara klassifierare för att hantera en varierande synvinkel. Slutligen föreslår vi en klassifierare baserad på logiska grindar som ett generiskt sätt att hantera stor intraklassvariation i kombination med stor bakgrundsklass. Vi utvärderar alla föreslagna svaga klassificerare på publika datamängder för att underlätta jämförelse med andra metoder.
QC 20120110
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Rye, Jan-Michael. "Spatial Modulation Spectroscopy Of Single Nano-Objects In A Liquid Environment For Biosensing Applications." Thesis, Lyon, 2017. http://www.theses.fr/2017LYSE1053/document.
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Le développement de méthodes rapides, précises et ultra-sensibles pour la détection d'analytes cibles en solution est crucial pour la recherche et les applications potentielles en médecine ou biologie moléculaire. Une approche très prometteuse consiste à développer des nano-capteurs à partir de nano-objets métalliques (NOM) qui présentent une résonance d'extinction dans leur réponse optique. Cette résonance nommée résonance de plasmon de surface localisée (RPSL) peut être ajustée spectralement en jouant sur la nature, la morphologie et l'environnement du NOM. Mesurer des modifications sur la RPSL de nano-objets individuels en présence d'analytes cibles doit permettre de s'affranchir des effets de moyennes dans les mesures d'ensemble. De plus, cela ouvre la voie vers le développement d'échantillons micrométriques pour des tests multicibles sans étiquette (« label-free »).Dans ce travail on a développé un nouveau dispositif expérimental basé sur la technique de spectroscopie à modulation spatiale (SMS) permettant de sonder la réponse optique de NOM individuels en milieu liquide. En parallèle des méthodes de synthèse ont été mises au point pour obtenir des échantillons sondes stables permettant des mesures sur NOM unique, en particulier sur des bipyramides d'or qui présentent de nombreuses qualités intrinsèques faisant d'elles de bonnes candidates pour le « bio-sensing ».Des mesures ont été réalisées dans des environnements d'indice variable et les changements détectés sont en bon accord avec les simulations théoriques. De plus, de nombreuses études ont été réalisées pour comprendre l'influence des nombreux paramètres agissant sur la réponse optique des systèmes étudiésAdvances in the development of rapid, accurate and highly sensitive methods for detecting target analytes in solution will provide crucial tools for research and applications in medicine and molecular biology. One of the currently most promising approaches is the development of nanosensors based on the localized surface plasmon resonance (LSPR) of noble metal nano-objects (MNOs), which is an optical response that depends on their size, shape, composition and local environment. The ability to measure the modification of the reponse of a single MNO in the presence of a target analyte would allow each object to act as an independent probe with increased sensitivity as the signal would be isolated from the averaging effects of ensemble measurements. Furthermore it would allow the development of micrometric, functionalized multiprobe samples for multitarget label-free assays.In this work, a novel experimental setup based on the spatial modulation spectroscopy (SMS) technique has been developed to measure the optical response of individual nano-objects in a liquid environment. In parallel, a new technique has also been developed to elaborate stable probes for measurements with the new setup, with a focus on gold bipyramids due to numerous qualities that make them excellent candidates for biosensing probes. The setup has been used to measure the response of individual objects in environments of different real refractive indices and the detected changes have been shown to be in good agreement with theoretical calculations. Numerical studies have also been performed to investigate the influence on the optical response of numerous factors encountered in the studied systems
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Jančeková, Lucie. "Polyfunkční objekt, Přerov." Master's thesis, Vysoké učení technické v Brně. Fakulta stavební, 2013. http://www.nusl.cz/ntk/nusl-226113.
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The topic of this Master's thesis is an elaboration of project documentation of construction part for a project of new building polyfunctional object in Přerov. Object is composed of three floors. In the first floor there are shops and café. In the second and third floor there are office areas. Construction system is transverse wall. The ceilings are made of prestressed panels. The roof of polyfunctional object is single-layer flat roof.
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Shortell, Laurel Lynn. "The healthy solitary person : a project based on an independent investigation /." View online, 2008. http://hdl.handle.net/10090/5926.
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Lee, Chee Sing. "Simultaneous localization and mapping using single cluster probability hypothesis density filters." Doctoral thesis, Universitat de Girona, 2015. http://hdl.handle.net/10803/323637.
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The majority of research in feature-based SLAM builds on the legacy of foundational work using the EKF, a single-object estimation technique. Because feature-based SLAM is an inherently multi-object problem, this has led to a number of suboptimalities in popular solutions. We develop an algorithm using the SC-PHD filter, a multi-object estimator modeled on cluster processes. This algorithm hosts capabilities not typically seen with feature-base SLAM solutions such as principled handling of clutter measurements and missed detections, and navigation with a mixture of stationary and moving landmarks. We present experiments with the SC-PHD SLAM algorithm on both synthetic and real datasets using an autonomous underwater vehicle. We compare our method to the RB-PHD SLAM, showing that it requires fewer approximations in its derivation and thus achieves superior performance.En aquesta tesis es desenvolupa aquest algoritme a partir d’un filtre PHD amb un únic grup (SC-PHD), una tècnica d’estimació multi-objecte basat en processos d’agrupació. Aquest algoritme té unes capacitats que normalment no es veuen en els algoritmes de SLAM basats en característiques, ja que és capaç de tractar falses característiques, així com característiques no detectades pels sensors del vehicle, a més de navegar en un entorn amb la presència de característiques estàtiques i característiques en moviment de forma simultània. Es presenten els resultats experimentals de l’algoritme SC-PHD en entorns reals i simulats utilitzant un vehicle autònom submarí. Els resultats són comparats amb l’algoritme de SLAM Rao-Blackwellized PHD (RB-PHD), demostrant que es requereixen menys aproximacions en la seva derivació i en conseqüència s’obté un rendiment superior.
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Schennings, Jacob. "Deep Convolutional Neural Networks for Real-Time Single Frame Monocular Depth Estimation." Thesis, Uppsala universitet, Avdelningen för systemteknik, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-336923.
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Vision based active safety systems have become more frequently occurring in modern vehicles to estimate depth of the objects ahead and for autonomous driving (AD) and advanced driver-assistance systems (ADAS). In this thesis a lightweight deep convolutional neural network performing real-time depth estimation on single monocular images is implemented and evaluated. Many of the vision based automatic brake systems in modern vehicles only detect pre-trained object types such as pedestrians and vehicles. These systems fail to detect general objects such as road debris and roadside obstacles. In stereo vision systems the problem is resolved by calculating a disparity image from the stereo image pair to extract depth information. The distance to an object can also be determined using radar and LiDAR systems. By using this depth information the system performs necessary actions to avoid collisions with objects that are determined to be too close. However, these systems are also more expensive than a regular mono camera system and are therefore not very common in the average consumer car. By implementing robust depth estimation in mono vision systems the benefits from active safety systems could be utilized by a larger segment of the vehicle fleet. This could drastically reduce human error related traffic accidents and possibly save many lives. The network architecture evaluated in this thesis is more lightweight than other CNN architectures previously used for monocular depth estimation. The proposed architecture is therefore preferable to use on computationally lightweight systems. The network solves a supervised regression problem during the training procedure in order to produce a pixel-wise depth estimation map. The network was trained using a sparse ground truth image with spatially incoherent and discontinuous data and output a dense spatially coherent and continuous depth map prediction. The spatially incoherent ground truth posed a problem of discontinuity that was addressed by a masked loss function with regularization. The network was able to predict a dense depth estimation on the KITTI dataset with close to state-of-the-art performance.
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Prabhakar, Yadu. "Detection and counting of Powered Two Wheelers in traffic using a single-plane Laser Scanner." Phd thesis, INSA de Rouen, 2013. http://tel.archives-ouvertes.fr/tel-00973472.
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The safety of Powered Two Wheelers (PTWs) is important for public authorities and roadadministrators around the world. Recent official figures show that PTWs are estimated to represent only 2% of the total traffic but represent 30% of total deaths on French roads. However, as these estimated figures are obtained by simply counting the number plates registered, they do not give a true picture of the PTWs on the road at any given moment. This dissertation comes under the project METRAMOTO and is a technical applied research work and deals with two problems: detection of PTWsand the use of a laser scanner to count PTWs in the traffic. Traffic generally contains random vehicles of unknown nature and behaviour such as speed,vehicle interaction with other users on the road etc. Even though there are several technologies that can measure traffic, for example radars, cameras, magnetometers etc, as the PTWs are small-sized vehicles, they often move in between lanes and at quite a high speed compared to the vehicles moving in the adjacent lanes. This makes them difficult to detect. the proposed solution in this research work is composed of the following parts: a configuration to install the laser scanner on the road is chosen and a data coherence method is introduced so that the system is able to detect the road verges and its own height above the road surface. This is validated by simulator. Then the rawd ata obtained is pre-processed and is transform into the spatial temporal domain. Following this, an extraction algorithm called the Last Line Check (LLC) method is proposed. Once extracted, the objectis classified using one of the two classifiers either the Support Vector Machine (SVM) or the k-Nearest Neighbour (KNN). At the end, the results given by each of the two classifiers are compared and presented in this research work. The proposed solution in this research work is a propototype that is intended to be integrated in a real time system that can be installed on a highway to detect, extract, classify and counts PTWs in real time under all traffic conditions (traffic at normal speeds, dense traffic and even traffic jams).
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Přibyl, Bronislav. "Odhad parametrů objektů z obrazů." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2010. http://www.nusl.cz/ntk/nusl-235537.
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Rapid expansion of communication technologies in last decade caused increased volume of information which is beeing generated and shared by people and organisations. It is permanently harder to identify relevant content today because of absence of tools and techniques which may support mass information management. As today's media have rather multimedial character image information is even more important. This project describes software for automatic estimation of predefined object parameters from images. A C++ implementation of this algorithm is also described.
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Kjellström, Johan, and Anton Drugge. "Kan val av JavaScript-ramverk påverkaanvändarupplevelsen? : En jämförelse mellan Vue och Svelte." Thesis, Luleå tekniska universitet, Institutionen för system- och rymdteknik, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-86085.
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Under de senaste decennierna har webben utvecklats allt mer, och är idag en stor del av människors vardag. Det finns idag över 1,8 miljarder webbplatser i bruk, och över 97% av dessaanvänder sig av JavaScript som programmeringsspråk för klientsidan. Människans koncentrationsförmåga har också minskat genom åren, och det ställs idag allt högre krav på snabba responstider på webben. Användarupplevelsen är också väldigt viktig för att en webbplats ska lyckas med sitt ändamål. Vi har i vår studie valt att undersöka och jämföra prestandan i JavaScript-ramverken Svelte och Vue, där vi ville studera eventuella prestandaskillnader med särskild fokus på responstider. Vi ville även undersöka om eventuella prestandaskillnader kunde upplevas av användarna vid olika typer av manipulationer av DOMen, såsom exempelvis tillägg och borttagning av HTML-elementet <div> i både större och mindre skala, och således påverka användarupplevelsen. Vi utvecklade två stycken single-page-applikationer som använder sig utav JavaScript, där den ena använder sig av Vue och den andra utav Svelte som frontend-ramverk, för att sedan utföra prestandatester på bägge webbplatserna. Därefter lät vi en grupp användare testa webbplatserna för att sedan svara på en enkät, där enkätfrågorna fokuserade på hur de upplevde prestandan ochom de kunde märka någon skillnad mellan applikationerna. Datainsamlingen för att kunna besvara de andra parametrarna för ramverken som denna studieämnade att undersöka, som går under användbarhet, skedde genom att skicka ut en enkät där vi lät både professionella frontend-utvecklare samt utvecklare på hobbynivå med erfarenhet av både Svelte och Vue besvara ett antal frågor om användbarhet. Slutsatsen av studien mynnar ut i att prestandaskillnader mellan ramverken i våra single-page-applikationer existerar, och kan i vissa fall också märkas av användarna. Om utvecklarna själva får bestämma vilket ramverk de föredrar väljer de professionella utvecklarna att arbeta med Vue och hobbyutvecklarna Svelte. För den officiella dokumentationen tenderade båda respondentgrupperna att föredra Vue över Svelte.
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Antl, Petr. "Objekt občanského vybavení." Master's thesis, Vysoké učení technické v Brně. Fakulta stavební, 2019. http://www.nusl.cz/ntk/nusl-392032.
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The aim of the diploma thesis was to draw up a proposal for the project documentation for the realization of the construction of the civic amenities building and that of the sports center. The building is located in Prostějov, cadastral area Prostějov. It is a three-storey building with one underground and two above-ground floors. Across the floors there are spaces for various sports uses, technical background of the building, staff backgrounds and a café. The object is based on the base passages, the vertical structures are formed by blocks of lost formwork and ceramic cavity blocks, the ceiling structures are solved by pre-stressed ceiling panels. The roof is designed as a single-layer, flat with extensive vegetation treatment, the roofing of the roof is finished by means of atics. The project is designed with an emphasis on the layout and constructional design of the building with respect to the parties and the land plan. During the processing I tried to use modern building materials and procedures and to process the building as a functioning unit.
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Zarov, Filipp. "Modeling fault probability in single railroad turnouts in Eastern Region, Sweden, with the use of logistic regression models : A step from preventive to predictive preventive maintenance in railway maintenance planning." Thesis, KTH, Transportplanering, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-273639.
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Turnouts are an important part of railway infrastructure for two reasons: infrastructure andmaintenance. For the infrastructure they provide the flexibility to allow the formulation and branchingof railway network and for maintenance they consume a large part of maintenance budget and have aprominent place in maintenance planning policy and activities. This is because as a “mechanical object”,a turnout often experiences malfunctions. The problem becomes even more complicated, since a turnoutis composed of many different parts and each of them fails for very different reasons (e.g. switch bladesvs crossing part). This is reflected in the different needs for maintenance activities, as railways areforced to pour in excessive amounts of resources to carry out emergency repairs, or to carry outunnecessary scheduled maintenance works in turnouts, which do not need to be inspected or repaired.Therefore, it is difficult to plan and organize maintenance activities in turnouts in an efficient manner.This raises the question of whether malfunctions in turnouts can be predicted and used as informationfor the maintenance planning process in order to optimize it and develop it into a more reliablepreventive maintenance planning.The aim of this analysis is to attempt to model the probability of various malfunctions in turnouts asa function of their main geometric and operational characteristics by using logistic regression modelsand then input these results into the maintenance planning process in order to optimize it. First, it wasimportant to objectify the railway track system and the turnout components, both in terms of parts andinterrelationships. Furthermore, the process and basic elements of railway maintenance planning weredefined, as well as arguments that motivate a turn towards preventive maintenance planningmethodologies. This was done through a comprehensive literature study.The basis of this research was case studies, which described the relationship between geometricaland operational characteristics of turnouts and their wear, as well as risk-based modelling methods inrailway maintenance planning. To create the analysis model, data from turnouts in eastern regionprovided by the Swedish Transport Administration were used, both from the point of view of describingthe underlying causes of turnout malfunctions and to formulate an object-oriented database suitable forusing in logistic regression models. The goal was a logit model that calculated the malfunctionprobability of a turnout, which could be used directly into a maintenance planning framework, whichranked maintenance activities in turnouts.The results obtained showed that although the model suffers from low correlation, differentrelationships between input variables and different functional errors were established. Furthermore, thepotential of these analytical models and modeling structures was shown to be able to developpreventive, predictive railway maintenance plans, but further analysis of the data structure is required,especially regarding data quality. Finally, further possible research areas are presented.Spårväxlar är viktiga delar av järnvägens infrastruktur av två orsaker: infrastruktur och underhåll.För infrastrukturen ger de möjlighet till flexibla tillåter de formulering och grenning av järnvägsnät ochför underhållet konsumerar de en stor del av underhållsbudgeten och de har en framträdande plats iunderhållsplaneringspolitiken och aktiviteterna. Detta beror på att som ett ”maskinellt objekt”, harspårväxeln ofta fel. Problemet blir ännu mer komplicerat, eftersom en spårväxel består av många olikadelar och var och en av dem bryts ner av mycket olika skäl (t.ex. tunganordning vs korsningsdel). Dettaåterspeglas i olika behov av underhållsaktiviteter. Eftersom järnvägarna tvingas hålla alltför storamängder resurser för att utföra akuta reparationer eller för att utföra onödiga schemalagdaunderhållsarbeten i spårväxlar, som inte behöver inspekteras eller repareras. Därför är det svårt attplanera och organisera underhållsaktiviteter för spårväxlarna på ett effektivt sätt. Detta ställer fråganom funktionsfel i spårväxlar kan förutsägas och användas som information till underhållsplaneringsprocessen för att optimera den och utveckla den till en pålitligare förebyggandeunderhållsplanering.Syftet med denna analys är att försöka modellera sannolikheten för olika funktionsfel i spårväxlarsom en funktion av deras huvudsakliga geometriska och operativa egenskaper med användning avlogistiska regressionsmodeller och sedan mata dessa resultat in i underhållsplaneringsprocessen för attoptimera den. För det första var det viktigt att objektifiera järnvägsspårsystemet ochspårväxlarkomponenterna, både vad gäller delar och inbördes förhållanden. Dessutom definieradesprocessen och grundelementen i järnvägsunderhållsplaneringen, samt att argument som motiverarförändring till förebyggande underhållsplaneringsmetoder. Detta gjordes genom en omfattandelitteraturstudie.Grunden i denna analys var fallstudier, som beskrev förhållandet mellan geometriska ochoperationella egenskaper hos spårväxlar och deras förslitning samt riskbaserade modelleringsmetoder ijärnvägsunderhållsplanering. För att skapa analysmodellen användes data från spårväxlar i östraregionen som tillhandahölls av Trafikverket, både ur synpunkten att beskriva de underliggandeorsakerna till spårväxlarsfel och för att formulera en objektorienterad databas lämplig för användning ilogistiska regressionsmodeller. Målet var en logitmodell som beräknade sannolikheten för fel i enspårväxel, som kunde användas direkt i en underhållsplaneringsram, som rangordnar lämpigaunderhållsaktiviteter i spårväxlar.Erhållna resultat visade att även om modellen lider av låg korrelation, konstaterades olika sambandmellan ingående variabler och olika funktionsfel. Vidare visades potentialen hos dessa analysmodelleroch modelleringsstrukturer för att kunna utveckla förebyggande, förutsägbarajärnvägsunderhållsplaner, men det krävs troligtvis ytterligare analys av datastrukturen, specielltangående datakvaliteten. Slutligen presenteras ytterligare möjliga forskningsområden.
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Výtisková, Jana. "Senior cohousing." Master's thesis, Vysoké učení technické v Brně. Fakulta stavební, 2015. http://www.nusl.cz/ntk/nusl-227285.
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Senior cohousing is situated in the Moravian-Silesian Region in city Orlová and it is designed as complex. It is a new form of living for seniors in the Czech Republic. The loose translation could be „close neighbourly living for senior people. “ Access road to the complex is from Tešínská Street and then down the main road from the southeast on the car park. Near the car park there are three main buildings. Building A is the main common building for seniors’ meetings. Building B has a private doctor and a small gym. Building C is designed as technical premises. There are four types of family houses for seniors. Family house type 1 - in the complex 3x is suitable for two seniors. Family house type 2 - in the complex 2x is suitable for two seniors with moving difficulties. Family house type 3 - in the complex 3x is designed as semi-detached house for two senior couples. Family houses accommodate 30 seniors in 15 housing units. All the objects are brick, single-storey without cellar built up from HELUZ system with footings from plain concrete with foundation slab, flat roofs, contact insulation of perimeter walls, partly wood tiling. What is more, in senior cohousing there are senior playground, orchard park, lake, road inside the complex, pavements and paths.
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Azizoglu, Suha Alp. "Time Domain Scattering From Single And Multiple Objects." Phd thesis, METU, 2008. http://etd.lib.metu.edu.tr/upload/12609413/index.pdf.
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The importance of the T-matrix method is well-known when frequency domain scattering problems are of interest. With the relatively recent and wide-spread interest in time domain scattering problems, similar applications of the T-matrix method are expected to be useful in the time domain. In this thesis, the time domain spherical scalar wave functions are introduced, translational addition theorems for the time domain spherical scalar wave functions necessary for the solution of multiple scattering problems are given, and the formulation of time domain scattering of scalar waves by two spheres and by two scatterers of arbitrary shape is presented. The whole analysis is performed in the time domain requiring no inverse Fourier integrals to be evaluated. Scattering examples are studied in order to check the numerical accuracy, and demonstrate the utility of the expressions.
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Everitt, Mark Julian. "Quantum dynamics and measurement of single quantum objects." Thesis, University of Sussex, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.310252.
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We consider the dynamics of Superconducting QUantum Interference Device (SQUID) rings in the presence of time dependent magnetic fields, solving the time dependent Schrodinger equation computationally. We compare the quantum mechanical behaviour of the SQUID ring with that of a simple two state system (the ammonia maser), finding close parallels between these two systems. We then consider the idea of measurement of macroscopic quantum objects by modelling the SQUID ring inductively coupled to a classical measurement device (a LC oscillator circuit). We solve the equations of motion for this coupled system both in the phenomenological Resistively Shunted Junction plus Capacitance (RSJ+C) model and within the framework of two models using a purely quantum mechanical SQUID ring.
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Braun, Marco, and Frank Cichos. "Gold nanostructure assisted thermophoretic trapping of single nano-objects." Universitätsbibliothek Leipzig, 2015. http://nbn-resolving.de/urn:nbn:de:bsz:15-qucosa-183290.
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Braun, Marco, and Frank Cichos. "Gold nanostructure assisted thermophoretic trapping of single nano-objects." Diffusion fundamentals 20 (2013) 62, S. 1, 2013. https://ul.qucosa.de/id/qucosa%3A13639.
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Nisbet-Jones, Peter. "Shaping single photons." Thesis, University of Oxford, 2012. http://ora.ox.ac.uk/objects/uuid:c75d4896-c5a8-42b8-a166-ffcd4166fc09.
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The possibility of creating a scaleable quantum network by interconverting photonic and atomic qubits shows great promise. The fundamental requirement for such a network is deterministic control over the emission and absorption of photons from single atoms. This thesis reports on the experi-mental construction of a photon source that can emit single-photons with arbitrary spatio-temporal shape, phase, and frequency. The photon source itself is a strongly-coupled atom cavity system based on a single 87 Rb atom within a macroscopic high-finesse Fabry-Perot cavity. It operates intermittently for periods of up to 100µs, with single-photon repetition rates of 1.0 MHz and an efficiency of almost 80%. Atoms are loaded into the cavity using an atomic fountain, with the upper turning point near the centre of the cavity mode. This ensures long interaction times without any disturbances introduced by trapping potentials. The photons’ indistinguishability was tested, with a two-photon Hong-Ou-Mandel visibility of 87%. This ability to both generate, and control, the photons’ properties, for example producing photons with symmetric or multi-peaked spatio-temporal shapes, allows for the production of photons in an n-time-bin superposition state where each time-bin has an arbitrarily defined amplitude and phase. These photons can be used as photonic qubits, qutrits and qquads, and their properties have been tested using a small linear-optics network.
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Chleborad, Aaron A. "Grasping unknown novel objects from single view using octant analysis." Thesis, Manhattan, Kan. : Kansas State University, 2010. http://hdl.handle.net/2097/4089.
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Braun, Marco. "Optically Controlled Manipulation of Single Nano-Objects by Thermal Fields." Doctoral thesis, Universitätsbibliothek Leipzig, 2016. http://nbn-resolving.de/urn:nbn:de:bsz:15-qucosa-206342.
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This dissertation presents and explores a technique to confine and manipulate single and multiple nano-objects in solution by exploiting the thermophoretic interactions with local temperature gradients. The method named thermophoretic trap uses an all-optically controlled heating via plasmonic absorption by a gold nano-structure designed for this purpose. The dissipation of absorbed laser light to thermal energy generates a localized temperature field. The spatial localization of the heat source thereby leads to strong temperature gradients that are used to drive a particle or molecule into a desired direction. The behavior of nano-objects confined by thermal inhomogeneities is explored experimentally as well as theoretically.
The monograph treats three major experimental stages of development, which essentially differ in the way the heating laser beam is shaped and controlled. In a first generation, a static heating of an appropriate gold structure is used to induce a steady temperature profile that exhibits a local minimum in which particles can be confined. This simple realization illustrates the working principle best. In a second step, the static heating is replaced. A focused laser beam is used to heat a smaller spatial region. In order to confine a particle, the beam is steered in circles along a circular gold structure. The trapping dynamics are studied in detail and reveal similarities to the well-established Paul trap. The largest part of the thesis is dedicated to the third generation of the trap. While the hardware is identical to the second generation, using the real-time information on the position of the trapped object to heat only particular sites of the gold structure strongly increases the efficiency of the trap compared to the earlier versions. Beyond that, the optical feedback control allows for an active shaping of the effective virtual trapping potential by applying modified feedback rules, including e.g. a double-well or a box-like potential. This transforms the formerly pure trapping device to a versatile technique for micro and nano-fluidic manipulation. The physical and technical contributions to the limits of the method are explored. Finally, the feasibility of trapping single macro-molecules is demonstrated by the confinement of lambda-DNA for extended time periods over which the molecules center-of-mass motion as well as its conformational dynamics can be studied.
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Vavassori, Luca. "SSC: Single-Shot Multiscale Counter. : Counting Generic Objects in Images." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-264236.
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Counting object in pictures is a computer vision task that has been explored in the past years, achieving state-of-the-art results thanks to the rise of convolutional neural networks. Most of the work focused on specific and limited domains to predict the number of just one category in the likes of people, cars, cells, and animals. Little effort has been employed to investigate methods to count the instances of different classes at the same time. This thesis work explored the different approaches present in the literature to understand their strenghts and weaknesses and eventually improve the accuracy and reduce the inference time of models aimed to estimate the number of multiple elements. At first, new techniques have been applied on top of the previously proposed algorithms to lower the prediction error. Secondly, the possibility to adapt an object detector to the counting task avoiding the localization prediction has been investigated. As a result, a new model called Single-Shot Multiscale Counter has been proposed, based on the architecture of the Single-Shot Multibox Detector. It achieved a lower prediction error on the ground truth count by 11% (from an mRMSE of 0.42 to 0.35) and an inference time 16x to 20x faster compared to the models found in the literature (from 1.25s to 0.049s).Att räkna objekt i bilder är en datorvisionsuppgift som har utforskats under de senaste åren och uppnått toppmoderna resultat tack vare ökningen av invändiga neurala nätverk. De flesta av arbetena fokuserade på specifika och begränsade domäner för att förutsäga antalet bara en kategori som människor, bilar, celler och djur. Liten ansträngning har använts för att undersöka metoder för att räkna förekomsten av olika klasser samtidigt. Detta avhandlingsarbete utforskade de olika metoder som finns i litteraturen för att förstå deras styrka och svagheter och så småningom förbättra noggrannheten och minska inferingstiden för modeller som syftar till att uppskatta antalet flera element. Först har nya tekniker tillämpats ovanpå de tidigare föreslagna algoritmerna för att sänka förutsägelsefelet. För det andra har möjligheten att anpassa en objektdetektor till räkneuppgiften för att undvika lokaliseringsförutsägelse undersökts. Som ett resultat har en ny modell som heter Single-Shot Multiscale Counter föreslagits, baserad på arkitekturen för Single-Shot Multibox Detector. Den uppnådde ett lägre förutsägelsefel på sanningsräkningen på marken med 11 % (från en mRMSE på 0,42 till 0,35) och en slutningstid 16x till 20x snabbare jämfört med modellerna som finns i litteraturen (från 1,25 till 0,049 sek).
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Weatherill, Eve Elizabeth. "Combining single-molecule fluorescence and single-channel recording in droplet interface bilayers." Thesis, University of Oxford, 2015. https://ora.ox.ac.uk/objects/uuid:99610130-0550-4dd9-b6ee-6ce2297a5bb9.
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Single-channel recordings (SCR) and single-molecule Fluorescence (SMF) are invaluable tools for studying membrane proteins. Combining these two techniques would allow for structural dynamics to be correlated with function at the single-molecule level. However, the different requirements of SCR and SMF measurements present a long-standing challenge. Droplet interface bilayers (DIBs) are a model membrane system in which parallelisation of such measurements is possible using optical single-channel recording to resolve the conductance of multiple proteins simultaneously. In this project, two approaches were evaluated for obtaining simultaneous measurements in DIBs: the first sought to report on structural changes associated with a gating bacterial mechanosensitive channel, MscS; the second sought to resolve kinetics of the spontaneous β-barrel folding mechanism. For both approaches, functional, labelled protiens were produced and characterised using ensemble measurements to confirm that the state-transition of interest was accompanied by a change in fluorescent signal. Characterisation of MscS in DIBs revealed that control of lateral tension (a requirement to stimulate mechanosensitive channel gating) posed a major experimental challenge, rendering further pursuit of this candidate impossible. However in the case of β-barrel folding, the single-molecule fluorescence alone revealed a rare but fast transition from a membrane-associated unfolded to a folded state. While further work is needed to fully exploit simultaneous measurements, significant progress towards this goal is presented in this work, in particular the development of reagents, experimental procedures and analytical tools.
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Han, Qiong Pizer Stephen M. "Proper shape representation of single figure and multi-figure anatomical objects." Chapel Hill, N.C. : University of North Carolina at Chapel Hill, 2008. http://dc.lib.unc.edu/u?/etd,2055.
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Thesis (Ph. D.)--University of North Carolina at Chapel Hill, 2008.Title from electronic title page (viewed Feb. 17, 2009). "... in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Department of Computer Science." Discipline: Computer Science; Department/School: Computer Science.
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Li, Xiuting. "Electrochemistry of single nanoparticles." Thesis, University of Oxford, 2017. https://ora.ox.ac.uk/objects/uuid:1ea3a662-242d-4734-a4da-25765fad4427.
Full textAbstract:
This thesis presents experimental work with two main aims: one is the detection and characterization of single electrocatalytic nanoparticles with an emphasis on metal nanoparticle decorated carbon nanotubes, and the other is to develop a more comprehensive understanding of nanoscale electrocatalysis by exploring the differences in the electrocatalytic behaviour of single nanotubes as compared to their ensembles. The first chapter introduces the basic principles and techniques of electrochemistry and the second chapter gives a brief introduction to the nanomaterials and electrochemical methods used in this thesis. Chapter 3 first reports the detection of individual carbon nanotubes with the 'nano-impact' method using the production of the under-potential deposited hydrogen (HUPD) from proton reduction on palladium nanoparticle decorated carbon nanotubes (CNT-Pds). The current spikes corresponding to the reduction of proton forming HUPD on the individual impacting CNT-Pds were detected via chronoamperometry. From the knowledge of the palladium nanoparticle sizes and their coverage on the CNTs it was further demonstrated how the magnitude of impact charge allows an assessment of the nanotube lengths. The correspondence between electrochemical sizing and microscopy results directly shows that a CNT-Pd is electroactive along its entire length, evidencing the reactivity and conductivity of the CNTs and further indicating the complete HUPD saturation of the palladium nanoparticles decorated on the carbon nanotubes. Chapter 4 then extends electrocatalytic nano-impacts of single CNT-Pd to investigate the hydrogen oxidation reaction (HOR). A facile procedure which enables rapidly and easily gathering single nanotube voltammetry was established and validated. Single CNT-Pds impact a micro wire electrode from dilute suspension and adhere to it for a sufficiently long time for cyclic voltammetry to be conducted. The single adsorbed decorated CNT is electro-catalytic towards HOR which thus occurs exclusively on it and cyclic voltammetry on single decorated carbon nanotube is realized. Single nanotube voltammetry of oxygen reduction reaction (ORR) was further studied and reported in Chapter 5. It demonstrates that the reduction of oxygen on Pd involves the initial formation of absorbed superoxide with fast electron transfer kinetics but with a low apparent transfer coefficient due to double layer effects arising from the Coulombic interactions of the adsorbed superoxide species inside the double layer. The mechanism of ORR on Pd was re-evaluated. Chapter 6 compares the oxidation of formate and of methanol at the single CNT-Pds and ensemble levels. Pd oxide formation as a competitive reaction with formate or methanol oxidation is significantly inhibited at high overpotentials at single nanotubes in comparison with what is seen with ensembles. The discovery of the superior electro-catalytic performance under high mass transport conditions created by single nanotubes suggests requirements for the design of better fuel cell development and offers the scope for new catalytic approaches to be developed. Chapter 7 is focused on the study of the origins of the current fluctuation observed in the single nanotube voltammetry by comparing the responses of HOR at a single CNT-Pds immobilised on the gold surface to analogous data on a carbon substrate. No significant distinction between the gold and carbon was found, demonstrating that the physical motion of the nanotube at the electrode is likely responsible for the modulation of current. A simple and feasible methodology based on the 'nano-impact' method is then developed to enable the measurement of the resistance across individual carbon nanotube-electrode contacts. It reveals that the major component of the measured resistance is associated with the single CNT-gold contact, which has major implications for the widespread use of CNTs as electro-catalysts and as catalyst supports.