Dissertations / Theses on the topic 'Local detection'
Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles
Consult the top 50 dissertations / theses for your research on the topic 'Local detection.'
Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.
You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.
Browse dissertations / theses on a wide variety of disciplines and organise your bibliography correctly.
Marín, Tur Javier. "Pedestrian Detection based on Local Experts." Doctoral thesis, Universitat Autònoma de Barcelona, 2013. http://hdl.handle.net/10803/120187.
Full textDuring the last decade vision-based human detection systems have started to play a key role in multiple applications linked to driver assistance, surveillance, robot sensing and home automation. Detecting humans is by far one of the most challenging tasks in Computer Vision. This is mainly due to the high degree of variability in the human appearance associated to the clothing, pose, shape and size. Besides, other factors such as cluttered scenarios, partial occlusions, or environmental conditions can make the detection task even harder. Most promising methods of the state-of-the-art rely on discriminative learning paradigms which are fed with positive and negative examples. The training data is one of the most relevant elements in order to build a robust detector as it has to cope the large variability of the target. In order to create this dataset human supervision is required. The drawback at this point is the arduous effort of annotating as well as looking for such claimed variability. In this PhD thesis we address two recurrent problems in the literature. In the first stage, we aim to reduce the consuming task of annotating, namely, by using computer graphics. More concretely, we develop a virtual urban scenario for later generating a pedestrian dataset. Then, we train a detector using this dataset, and finally we assess if this detector can be successfully applied in a real scenario. In the second stage, we focus on increasing the robustness of our pedestrian detectors under partial occlusions. In particular, we present a novel occlusion handling approach to increase the performance of block-based holistic methods under partial occlusions. For this purpose, we make use of local experts via a RandomSubspaceMethod (RSM) to handle these cases. If the method infers a possible partial occlusion, then the RSM, based on performance statistics obtained from partially occluded data, is applied. The last objective of this thesis is to propose a robust pedestrian detector based on an ensemble of local experts. To achieve this goal, we use the random forest paradigm, where the trees act as ensembles an their nodes are the local experts. In particular, each expert focus on performing a robust classification of a pedestrian body patch. This approach offers computational efficiency and far less design complexity when compared to other state-of-the-artmethods, while reaching better accuracy.
Ahlgren, Filip. "Local And Network Ransomware Detection Comparison." Thesis, Blekinge Tekniska Högskola, Institutionen för datavetenskap, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-18291.
Full textAytekin, Caglar. "Geo-spatial Object Detection Using Local Descriptors." Master's thesis, METU, 2011. http://etd.lib.metu.edu.tr/upload/12613488/index.pdf.
Full textSaigo, Hiroto. "Local alignment kernels for protein homology detection." 京都大学 (Kyoto University), 2006. http://hdl.handle.net/2433/135936.
Full textBeare, Richard. "Image segmentation based on local motion detection /." Title page, contents and abstract only, 1997. http://web4.library.adelaide.edu.au/theses/09PH/09phb3684.pdf.
Full textDonnelley, Martin, and martin donnelley@gmail com. "Computer Aided Long-Bone Segmentation and Fracture Detection." Flinders University. Engineering, 2008. http://catalogue.flinders.edu.au./local/adt/public/adt-SFU20080115.222927.
Full textBERVANAKIS, GEORGE, and gberva@hotmail com. "DETECTION AND EXPRESSION OF BIOSYNTHETIC GENES IN ACTINOBACTERIA." Flinders University. School of Medicine, 2009. http://catalogue.flinders.edu.au./local/adt/public/adt-SFU20090531.033038.
Full textTrauchessec, Vincent. "Local magnetic detection and stimulation of neuronal activity." Thesis, Université Paris-Saclay (ComUE), 2017. http://www.theses.fr/2017SACLS301/document.
Full textInformation transmission in the brain occurs through ionic currents flowing inside the neuronal network. Understanding how the brain operates requires probing this electrical activity by measuring the associated electric or magnetic field. At the cellular scale, electrophysiology techniques are well mastered, but there is no tool to perform magnetophysiology. Mapping brain activity through the magnetic field generated by neuronal communication is done via magnetoencephalography (MEG). This technique is based on SQUIDs (Superconducting Quantum Interference Devices) that operate at liquid Helium temperature. This parameter implies to avoid any contact with living tissue and a shielding system that increases the distance between the neurons and the sensors, limiting spatial resolution. This thesis work aims at providing a new tool to performmagnetic recordings at the neuronal scale. The sensors developed during this thesis are based on the Giant Magneto-Resistance (GMR) effect. Operating at room temperature, they can be miniaturize and shaped according to the experiment, while exhibiting a sensitivity that allows to measure amplitude of 10⁻⁹ T. Before targeting neurons, the use of GMR-based sensors for magnetic recordings of biological activity has been validated through invitro experiments on the mouse soleus muscle. This biological system has been chosen because of its simple organization, allowing for a realistic modelling, and for its robustness, in order to get reliable and replicable results. The perfect agreement between the measurements and the theoretical predictions represents a consistent validation of the GMR technology for biological applications. Then a specially adapted needle-shaped probe carrying micron-sized GMR sensors has been developed for in-vivo experiment in cat visual cortex. The very first magnetic signature of action potentials inside the neuropil has been measured, paving the way towards magnetophysiology
Gill, Rupinder S. "Intrusion detection techniques in wireless local area networks." Thesis, Queensland University of Technology, 2009. https://eprints.qut.edu.au/29351/1/Rupinder_Gill_Thesis.pdf.
Full textGill, Rupinder S. "Intrusion detection techniques in wireless local area networks." Queensland University of Technology, 2009. http://eprints.qut.edu.au/29351/.
Full textRabbani, Seyedeh Parisa. "Effect of image variation on computer aided detection systems." Thesis, KTH, Skolan för teknik och hälsa (STH), 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-123546.
Full textRobbins, Benjamin John. "The detection of 2D image features using local energy." University of Western Australia. Dept. of Computer Science, 1996. http://theses.library.uwa.edu.au/adt-WU2003.0005.
Full textMora, Maria Alejandra Mol André. "Detection of longitudinal tooth fractures using Local Computed Tomography." Chapel Hill, N.C. : University of North Carolina at Chapel Hill, 2006. http://dc.lib.unc.edu/u?/etd,536.
Full textTitle from electronic title page (viewed Oct. 10, 2007). "... in partial fulfillment of the requirements for the degree of Master of Science in the Department of Diagnostic Sciences and General Dentistry, School of Dentistry." Discipline: Diagnostic Sciences and General Dentistry; Department/School: Dentistry.
Shakeel, Asif. "Enhanced squeezing in homodyne detection via local-oscillator optimization." Thesis, Massachusetts Institute of Technology, 1995. http://hdl.handle.net/1721.1/37025.
Full textZhang, Ziming. "Efficient object detection via structured learning and local classifiers." Thesis, Oxford Brookes University, 2013. https://radar.brookes.ac.uk/radar/items/420cfbee-bf00-4d53-be8b-04f83389994f/1.
Full textAndersson, Martina. "Local, intestinal biomarkers for early detection of colorectal cancer." Thesis, Uppsala universitet, Institutionen för farmaci, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-445701.
Full textBelmonte, Romain. "Facial landmark detection with local and global motion modeling." Thesis, Lille 1, 2019. http://www.theses.fr/2019LIL1I066/document.
Full textFacial landmark detection is an essential task for a large number of applications such as facial analysis (e.g., identification, expression, 3D reconstruction), human-computer interaction or even multimedia (e.g., content indexing and retrieval). Although many approaches have been proposed, performance under uncontrolled conditions is still not satisfactory. The variations that may impact facial appearance (e.g., pose, expression, illumination, occlusion, motion blur) make it a difficult problem to solve. In this thesis, a contribution to both the analysis of the performance of current approaches and the modeling of temporal information for video-based facial landmark detection is made. An experimental study is conducted using a video dataset to measure the impact of pose and expression variations on landmark detection. This evaluation highlights the most difficult poses and expressions to handle. It also illustrates the importance of a suitable temporal modeling to benefit from the dynamic nature of the face. A focus is then placed on improving temporal modeling to ensure consideration of local motion in addition to global motion. Several architectures are designed based on the two main models from the literature: coordinate regression networks and heatmap regression networks. Experiments on two datasets confirm that local motion modeling improves results (e.g. in the presence of expressions). These experiments are extended with a study on the complementarity between spatial and temporal information as well as local and global motion to improve the design of the proposed architectures. By leveraging these complementarities more effectively, competitive performance with current state-of-the-art approaches is achieved, despite the simplicity of the proposed models
Ma, Fei, and feim@csem flinders edu au. "Registration of mass-like objects in sequential mammograms using graph matching." Flinders University. School of Computer Science, Engineering & Mathematics, 2008. http://catalogue.flinders.edu.au./local/adt/public/adt-SFU20090323.155040.
Full textNgonmang, Kaledje Christel Blaise. "Detection and dynamic of local communities in large social networks." Thesis, Paris 13, 2014. http://www.theses.fr/2014PA132057/document.
Full textComplex networks arises in many contexts and applications : biology, transports, online social networks (ONS). Many recent applications deal with large amount of personal data. The links between peoples may reflect freindship, messaging, or some common interests. Entities in complex network, and espacially persons, tend to form communities. Here, a community can be defined as a set of entities interacting more between each other than with the rest of the network. The topic of community detection in large networks as been extensively studied during the last decades, following the seminal work by newman, who popularized the modularity criteria. However, most community detection algorithms assume that the network is entirely known and that is does not evolve with time. This is usually not true in real world applications. In this thesis, we start by proposing novel methods for local community identification (considering only the vicinity of a given node, without accessing the whole graph). Our algorithms experimentally outperform the state-of-art methods. We show how to use the local communities to enhance the prediction of a user's behaviour. Secondly, we propose some approaches to predict the evolution of the detected communities based on machine learning methods. Finally we propose a framework for storing and processing distributed social networks in a Big Data environment. The proposed methods are validated using (among others) real world data, provided by a industrial partner operating a major social network platform in France (40 millions of users)
Lee, Boon Chuan. "Local interaction simulation approach for damage detection with Lamb waves." Thesis, University of Sheffield, 2005. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.425488.
Full textWenngren, Wilhelm Sven Ingemar. "Local pulse wave velocity detection over an arterial segment using photoplethysmography." University of British Columbia, 2017. http://hdl.handle.net/2429/63867.
Full textApplied Science, Faculty of
Engineering, School of (Okanagan)
Graduate
Yu, Meng. "Facial feature detection and tracking with a 3D constrained local model." Thesis, University of St Andrews, 2010. http://hdl.handle.net/10023/2124.
Full textCaruso, Laure. "Giant magnetoresistance based sensors for local magnetic detection of neuronal currents." Thesis, Paris 6, 2015. http://www.theses.fr/2015PA066272/document.
Full textUnderstanding brain activity requires simultaneous recordings across spatial scales, from single-cell to brain-wide network. Measurements provide insights about the relationship between structures, functions and dynamics in neuronal circuits and assemblies. Electrophysiological techniques carry crucial information about the electrical activity within neurons. Locally probing the magnetic signature of this activity gives direct information about neuronal currents and the vectorial nature of magnetic measurements provides the directionality of neuronal ionic flux without disturbing it. Noticeably, the magnetic signature induced by the neuronal currents is accessible through Magneto EncephaloGraphy (MEG), which provides neuromagnetic field mapping outside the head using Superconducting QUantum Interference Devices (SQUIDs). However, local measurements of neuronal currents at cellular scale requires small and very sensitive devices. The purpose of the present thesis work is to develop a novel tool for neurophysiology, the magnetic equivalent of electrodes, named “magnetrodes”, are able to detect the local neuronal currents through magnetic detection. Recent advances in spin electronics have given rise to Giant MagnetoResistance (GMR) based sensors, which offer the possibility to be miniaturized and sensitive enough to detect very weak magnetic fields like those emitted by neurons at local scale (in the picotesla to nanotesla range). Two kinds of GMR based sensors have been developed throughout this work, one of these are planar probes dedicated to surface measurements (hippocampus slice, muscle or cortex), the other kind are sharp probes, designed in a needle-shape to easily penetrate the tissues and locally record the neuromagnetic fields. Three experiments have been performed, either in vitro and in vivo. In the first experiment, an Action Potential has been detected magnetically in vitro by means of planar GMR sensors, resulting from axial currents within a mouse muscle. The second in vitro experiment analyzed the hippocampal mouse brain slices, where both planar and sharp probes were tested giving some preliminary results. Lastly we performed the first magnetic recordings in vivo on cat's cerebral cortex, displaying stimulus-induced cortical responses of 10-20 nT pp . These results pave the way for local magnetophysiology, a novel approach of brain exploration and interfacing
Le, Viet Phuong. "Logo detection, recognition and spotting in context by matching local visual features." Thesis, La Rochelle, 2015. http://www.theses.fr/2015LAROS029/document.
Full textThis thesis presents a logo spotting framework applied to spotting logo images on document images and focused on document categorization and document retrieval problems. We also present three key-point matching methods: simple key-point matching with nearest neighbor, matching by 2-nearest neighbor matching rule method and matching by two local descriptors at different matching stages. The last two matching methods are improvements of the first method. In addition, using a density-based clustering method to group the matches in our proposed spotting framework can help not only segment the candidate logo region but also reject the incorrect matches as outliers. Moreover, to maximize the performance and to locate logos, an algorithm with two stages is proposed for geometric verification based on homography with RANSAC. Since key-point-based approaches assume costly approaches, we have also invested to optimize our proposed framework. The problems of text/graphics separation are studied. We propose a method for segmenting text and non-text in document images based on a set of powerful connected component features. We applied dimensionality reduction techniques to reduce the high dimensional vector of local descriptors and approximate nearest neighbor search algorithms to optimize our proposed framework. In addition, we have also conducted experiments for a document retrieval system on the text and non-text segmented documents and ANN algorithm. The results show that the computation time of the system decreases sharply by 56% while its accuracy decreases slightly by nearly 2.5%. Overall, we have proposed an effective and efficient approach for solving the problem of logo spotting in document images. We have designed our approach to be flexible for future improvements by us and by other researchers. We believe that our work could be considered as a step in the direction of solving the problem of complete analysis and understanding of document images
Okuyama, Satoshi. "Application of SAR interferometry to detection of local deformations in Izu-Oshima." 京都大学 (Kyoto University), 2006. http://hdl.handle.net/2433/144190.
Full text0048
新制・課程博士
博士(理学)
甲第12107号
理博第3001号
新制||理||1447(附属図書館)
23943
UT51-2006-J102
京都大学大学院理学研究科地球惑星科学専攻
(主査)教授 竹本 修三, 助教授 福田 洋一, 教授 橋本 学
学位規則第4条第1項該当
Madrigali, Andrea. "Analysis of Local Search Methods for 3D Data." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2016.
Find full textZheng, Lining. "Distributed Local Outlier Factor with Locality-Sensitive Hashing." Thesis, Université d'Ottawa / University of Ottawa, 2019. http://hdl.handle.net/10393/39817.
Full textSenthil, Rathna. "IDLE: A Novel Approach to Improving Overlapping Community Detection in Complex Networks." Thesis, Virginia Tech, 2016. http://hdl.handle.net/10919/65160.
Full textMaster of Science
Wang, Benjamin. "Lip Detection and Adaptive Tracking." DigitalCommons@CalPoly, 2017. https://digitalcommons.calpoly.edu/theses/1695.
Full textAli, Imtiaz. "Object Detection in Dynamic Background." Thesis, Lyon 2, 2012. http://www.theses.fr/2012LYO20008/document.
Full textMoving object detection is one of the main challenges in many video monitoring applications.In this thesis, we address the difficult problem that consists in object segmentation when background moves permanently. Such situations occur when the background contains water flow, smoke or flames, snowfall, rainfall etc. Object detection in moving background was not studied much in the literature so far. Video backgrounds studied in the literature are often composed of static scenes or only contain a small portion of moving regions (for example, fluttering leaves or brightness changes). The main difficulty when we study such situations is to differentiate the objects movements and the background movements that may be almost similar. For example, an object in river moves at the same speed as water. Therefore, motion-based techniques of the literature, relying on displacements vectors in the scene, may fail to discriminate objects from the background, thus generating a lot of false detections. In this complex context, we propose some solutions for object detection.Object segmentation can be based on different criteria including color, texture, shape and motion. We propose various methods taking into account one or more of these criteria.We first work on the specific context of wood detection in rivers. It is a part of DADEC project (Détection Automatique de Débris pour l’Aide à l’Etude des Crues) in collaboration with geographers. We propose two approaches for wood detection: a naïve method and the probabilistic image model. The naïve approach is based on binary decisions based on object color and motion, whereas the probabilistic image model uses wood intensity distribution with pixel motion. Such detection methods are used fortracking and counting pieces of wood in rivers.Secondly, we consider a context in which we suppose a priori knowledge about objectmotion is available. Hence, we propose to model and incorporate this knowledge into the detection process. We show that combining this prior motion knowledge with classical background model improves object detection rate.Finally, drawing our inspiration from methods used for 2D texture representation, we propose to model moving backgrounds using a frequency-based approach. More precisely, the model takes into account the spatial neighborhoods of pixels but also their temporal neighborhoods. We apply local Fourier transform on the obtained regions in order to extract spatiotemporal color patterns.We apply our methods on multiple videos, including river videos under DADEC project, image sequences from the DynTex video database, several synthetic videos andsome of our own made videos. We compare our object detection results with the existing methods for real and synthetic videos quantitatively as well as qualitatively
Gundogdu, Erhan. "Feature Detection And Matching Towards Augmented Reality Applications On Mobile Devices." Master's thesis, METU, 2012. http://etd.lib.metu.edu.tr/upload/12614618/index.pdf.
Full textin general, the main metrics are accepted as accuracy and computational complexity. The contributions in this thesis provide improving these metrics and can be divided into three parts, as local feature detection, local feature description and description matching in different views of the same scene. In this thesis an efficient feature detection algorithm with sufficient repeatability performance is proposed. This detection method is convenient for real-time applications. For local description, a novel local binary pattern outperforming state-of-the-art binary pattern is proposed. As a final task, a fuzzy decision tree method is presented for approximate nearest neighbor search. In all parts of the system, computational efficiency is considered and the algorithms are designed according to limited processing time. Finally, an overall system capable of matching different views of the same scene has been proposed and executed in a mobile platform. The results are quite promising such that the presented system can be used in real-time applications, such as augmented reality, object retrieval, object tracking and pose estimation.
Asbach, Mark [Verfasser]. "Modeling for part-based visual object detection based on local features / Mark Asbach." Aachen : Hochschulbibliothek der Rheinisch-Westfälischen Technischen Hochschule Aachen, 2012. http://d-nb.info/1021938211/34.
Full textHajdarevic, Kemal. "Early detection of network problems using existing network indicators : local agent based approach." Thesis, Leeds Beckett University, 2008. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.446160.
Full textMikolajczyk, Krystian. "Detection of local features invariant to affine transformations : application to matching and recognition." Grenoble INPG, 2002. http://www.theses.fr/2002INPG0053.
Full textJohansson, Stefan. "Earthquake Analysis Using a Migration Based Detection Algorithm Applied to Local Earthquake Data." Thesis, Uppsala universitet, Geofysik, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-325373.
Full textI denna studie analyserades jordskalvsdata med hjälp av en nyligen utvecklad 'migration based detection'-algoritm (Wagner et al. 2017). En mjukvarumiljö skräddarsydd för manuell analys av stora kvantiteter av jordskalv detekterade av MBD-algoritmen iordningställdes, varpå MBD-algoritmen sedan applicerades på 13 dagar av seismisk data från ett nätverk av 26 seismiska stationer i det geologiskt sett komplexa Hengill-området i sydvästra Island. Totalt detekterades 859 jordskalv som genomgick manuell analys. Av dessa klassificerades 483 stycken som bekräftade eller troliga jordskalv, vilket resulterar i en uppskattad felmarginal om ca. 44 %. En delmängd om 53 väldefinierade jordskalv valdes ut för noggrannare analys av ursprungsplats och tidpunkt genom manuell plockning av P-fasankomst. Omlokaliseringen resulterade i en genomsnittlig differens om ca. 0.6 km i vardera koordinat i horisontalplanet och ca. 1.4 km i höjdled. Resultat från projektet kan användas som referensdata vid vidareutveckling av MBD-algoritmen samt ger viss insyn i prestandan hos MBD-algoritmen. Den iordningställda datormiljön kan användas som bas för vidare analys av jordskalv detekterade av MBD-algoritmen.
Tran, Antoine. "Object representation in local feature spaces : application to real-time tracking and detection." Thesis, Université Paris-Saclay (ComUE), 2017. http://www.theses.fr/2017SACLY010/document.
Full textVisual representation is a fundamental problem in computer vision. The aim is to reduce the information to the strict necessary for a query task. Many types of representation exist, like color features (histograms, color attributes...), shape ones (derivatives, keypoints...) or filterbanks.Low-level (and local) features are fast to compute. Their power of representation are limited, but their genericity have an interest for autonomous or multi-task systems, as higher level ones derivate from them. We aim to build, then study impact of low-level and local feature spaces (color and derivatives only) for two tasks: generic object tracking, requiring features robust to object and environment's aspect changes over the time; object detection, for which the representation should describe object class and cope with intra-class variations.Then, rather than using global object descriptors, we use entirely local features and statisticals mecanisms to estimate their distribution (histograms) and their co-occurrences (Generalized Hough Transform).The Generalized Hough Transform (GHT), created for detection of any shape, consists in building a codebook, originally indexed by gradient orientation, then to diverse features, modeling an object, a class. As we work on local features, we aim to remain close to the original GHT.In tracking, after presenting preliminary works combining the GHT with a particle filter (using color histograms), we present a lighter and fast (100 fps) tracker, more accurate and robust.We present a qualitative evaluation and study the impact of used features (color space, spatial derivative formulation).In detection, we used Gall's Hough Forest. We aim to reduce Gall's feature space and discard HOG features, to keep only derivatives and color ones.To compensate the reduction, we enhanced two steps: the support of local descriptors (patches) are partially chosen using a geometrical measure, and node training is done by using a specific probability map based on patches used at this step.With reduced feature space, the detector is less accurate than with Gall's feature space, but for the same training time, our works lead to identical results, but with higher stability and then better repeatability
Perret, Matias Nicholas. "Local optical phase detection probes with an application to a high speed boundary layer." Diss., University of Iowa, 2016. https://ir.uiowa.edu/etd/2129.
Full textWu, Yubao. "Efficient and Effective Local Algorithms for Analyzing Massive Graphs." Case Western Reserve University School of Graduate Studies / OhioLINK, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=case1454451336.
Full textAlamgir, Nyma. "Computer vision based smoke and fire detection for outdoor environments." Thesis, Queensland University of Technology, 2020. https://eprints.qut.edu.au/201654/1/Nyma_Alamgir_Thesis.pdf.
Full textAbt, Tin Lian. "Detection of a Local Mass Anomaly in the Shallow Subsurface by Applying a Matched Filter." The Ohio State University, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=osu1313154731.
Full textWhite, Shane Paul White. "Study of Heavy Metal/Ferromagnetic Films Using Electrical Detection and Local Ferromagnetic Resonance Force Microscopy." The Ohio State University, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=osu1524172007784423.
Full textChen, Chuxing. "Local atmospheric electricity and its possible application in high-energy cosmic ray air shower detection." Diss., The University of Arizona, 1989. http://hdl.handle.net/10150/184799.
Full textChen, Shin-an, and 陳信安. "Local Sensor Fault Detection." Thesis, 2001. http://ndltd.ncl.edu.tw/handle/51467149371373062679.
Full text元智大學
電機工程研究所
89
This thesis investigates the problem of local sensor fault detection. The conventional approach is to filter out the low frequency normal signal with high pass filter before detection. We point out that detecting the sensor fault after high-pass filtering is problematic. For example, the energy of the fault signal “change of bias” is concentrate in low frequencies. After high-pass filtering, most of the energy disappears and the detection fails. We propose to use the unfiltered sensor output signal directly to detect sensor fault. Events like Bias-change, Noise-increase or Jump occurs can be detected by observing the sample mean、sample variance and normalized sample. Four types of sensor faults: Bias、Drift、Erratic and Spike can be detected based on the observations. In the simulations, we use both synthetic signals generated from a mathematical model and earthquake real-measured data to detect sensor faults. We also propose to use soft decisions that correspond to fault degrees between 0 and 1, which provide more information compare to the “0” or “1” hard decision.
張芝榮. "Relative Centrality and Local Community Detection." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/47791975490821202491.
Full textWu, Chan-Wei, and 吳展維. "Channel-Aware Distributed Binary Detection with Unknown Local Sensor Detection Probability." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/89795682750674031944.
Full text國立交通大學
電信工程系所
97
In the field of wireless sensor networks, existing works of channel-aware fusion rule design assume that the fusion center (FC) knows the local sensor detection probabilities. However, this paradigm ignores the possibility of unknown sensor alarm responses to the event occurrences. This work focuses on the case where the local detection probability is unknown and assumes sensors transmit their one-bit reports through binary symmetric channels to FC. Traditionally, Generalized Likelihood Ratio Test (GLRT) can tackle this scenario, but it does not guarantee optimal performance and is too complicated to analyze. To solve these problems, a simpler fusion rule is proposed based on the simplified ML estimate, and its performance is analyzed. By investigating the channel effects, a power allocation scheme is then proposed to further improve the performance. Being far less complicated than GLRT, the proposed fusion rule with power allocation outperforms GLRT significantly and can even achieve the performance of LRT, which is the optimal rule for any possible detectors.
Peng, Shen-Chieh, and 彭聖傑. "Smoke Detection Using Global and Local Features." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/35942372244330965413.
Full text國立交通大學
生醫工程研究所
99
This study presents a novel smoke detection approach using local feature analysis and global feature verification. Studies have investigated visual-based smoke detection techniques in surveillance systems for years. However, given an image in open or large spaces with typical smoke and disturbances of commonly moving objects such as pedestrians or vehicles, detecting smoke without false alarm is still a challenging problem. It is important to find features to distinguish smoke from various environments. This study analyzes characteristics of candidate blocks in video sequences to exploit local features: edge blurring, gradual energy change and gradual color configuration change. Each local feature is strong enough to detect smoke with few false alarms. Moreover, proposed features are complementary to each other. Hence, local features are combined to lower the false alarm rates by boosting cascade architecture. To further overcome some false situation, global feature verification is proposed to gather statistics of information on contour and in the whole area of each candidate region. Experimental results show that the proposed system can well detect smoke with low false alarm rate within a short reaction time in various environments. The whole system can run in real time and has been implemented on embedded system.
Chen, Jung-Bow, and 陳中寶. "Face detection based on local color texture." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/09578835892851533958.
Full text玄奘大學
資訊科學學系碩士班
95
In biometrics authentication, face recognition is usually used as the core technology, and face detection is one of the most important work in face recognition. The main propose in face detection is to use the image to find if a subimage is the human’s face or not and to draw the existence area, so that it is easier to do further recognition works. In the literature, there have many methods to execute the task of the face detection. For example, they are Template matching, Neural network approach, Color-based approach, etc, but only a few of them use the feature of the color texture in face detection. They proposed Color Wavelet Covariance (CWC) and Wavelet Transform (WT) technologies and bringing out the suitable method for face detection. A method which can use the specific color texture feature on the face, is proposed in this paper. Using statistic measures to find out the color texture vector, the support vector machine (SVM) classifier is used to discriminate faces and non-faces. The support vector machine can be used to complete a complicated static image, and to provide a effective face detection.
Zhi-JiaJian and 簡志佳. "CLOSE: Local Community Detection by LOcal Structure Expansion in a Complex Network." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/8vf89j.
Full textHuang, Ssu-Neng, and 黃偲能. "Region Duplication Detection Based on Image Invariant Feature and Local Outlier Detection." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/mb82u9.
Full text國立臺北科技大學
電機工程系研究所
99
Nowadays image editing software is so sophisticated that one can easily tamper digital images without leaving any obvious traces. To develop an automatic tampering detection algorithm becomes an important issue. Region duplication is a common and simple way of digital image tampering. Recent methods based on sparse feature descriptor matching can detect the region duplication with lower geometrical and illumination distortion, where past methods could fail, but they are still imperfect for the detection of duplicated regions imposed with stronger distortion of affine transform and rotation. Furthermore, all the existing methods will mistakenly classify the intrinsic repeated elements as duplication tamping. Our method stems from sparse feature descriptor matching approach. We propose a new matching method for higher distortion and a local outlier detection method to analyze the distribution of image invariant feature on image space for intrinsic repeated elements. We evaluate our proposed approach on a set of automatically synthesized forgery images with duplicated, distorted regions and intrinsic repeated elements. The experimental results show that our proposed method is robust and effective in region duplication detection.
Tao, Chun-Hao, and 陶君浩. "Compare the Detection Result by Using Different Local Item Dependent Detection Methods." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/81568550699907328582.
Full text國立臺灣師範大學
教育心理與輔導學系
101
The purpose of this research is to compare the detection result by using testlet effect estimates of the Rasch testlet model, testlet-residual based principal component analysis and the Q3 statistics. The research is composed of two sub-researches. Study 1 is a simulation study. In study 1, first, testlet effects (high/ low), sample sizes (500/1500) and the item numbers within testlet (2/4/6/8) were manipulated. Testlet effect estimates of the Rasch testlet model, testlet-residual based principal component analysis and the Q3 statistics were used to detected local item dependent for each testlet. The parameters recovery of testlet effect, the detection result of testlet-residual based principal component analysis and the Q3 statistics, and the Spearman's ρ coefficient of local item dependent detection result with the true value of testlet effect were used to compare the detection result of different local item dependent detection methods. Study 2 is an empirical study. These three local item dependent detection methods were compared and applied to the data from the English subject of Basic Competence Test for Junior High School Students(2004~2009). The main results are the following: 1.As sample sizes and the item numbers in each testlet were increased, the parameters recovery of testlet effect decreased to an acceptable level. It means the testlet effect estimates of the Rasch testlet model will be more and more accurate when the sample sizes or item numbers increases. However, in the condition of high testlet effect, the estimated accuracy of testlet effect were decreased instead. 2.No matter in what situations, the detection result of the Q3 statistics was better than the other two detection methods. 3.The detection results have varied between these three local item dependent detection methods on the english subject of Basic Competence Test for Junior High School Students(2004~2009), testlet effect estimates of the Rasch testlet model especially. 4.According to the detection result of the Q3 statistics, there were no local item dependent for each testlet on the english subject of Basic Competence Test for Junior High School Students(2004~2009), except for 93-2-3, 93-2-5, 93-2-6, 94-1-8, and 97-2-3 .