Dissertations / Theses on the topic 'Data fusion techniques'
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Carter, Duane B. "Analysis of Multiresolution Data fusion Techniques." Thesis, Virginia Tech, 1998. http://hdl.handle.net/10919/36609.
Full textMaster of Science
Glaab, Enrico. "Analysing functional genomics data using novel ensemble, consensus and data fusion techniques." Thesis, University of Nottingham, 2011. http://eprints.nottingham.ac.uk/12727/.
Full textAnsari, Abdul Wahab. "The control simulation of tactile sensors using constraint modelling techniques." Thesis, Brunel University, 1993. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.357684.
Full textDelgado, Prieto Miguel. "Contributions to electromechanical systems diagnosis by means data fusion techniques." Doctoral thesis, Universitat Politècnica de Catalunya, 2012. http://hdl.handle.net/10803/97043.
Full textEls accionaments electromecànics han tingut tradicionalment el seu camp d'aplicació en el sector industrial. No obstant això l'ús d'aquest tipus de sistemes s'està estenent cap a altres sectors dins l'àmbit dels transports, com el sector de l'automòbil, o el sector de l'aeronàutica, amb el desenvolupament del concepte de l'Avió Més Elèctric (MEA). Una de les millores més importants del concepte MEA està relacionada amb els actuadors dels controls primaris de vol, on fins ara només s'han considerat actuadors electrohidràulics, encara que la tendència actual és reemplaçar-los per actuadors electromecànics (EMA). L'ús generalitzat, en el futur, d'accionaments EMA en sistemes de transport, passa per la investigació i els avenços en els algorismes de detecció i diagnòstic de fallides que es puguin produir, tant en la part elèctrica com en la mecànica, per tal de garantir la fiabilitat de l'accionament i la seguretat dels usuaris. Durant els últims anys, l'estudi de sistemes electromecànics i el diagnòstic de fallides en diverses condicions de parell i de règim de funcionament, han estat estudiats profundament per diferents autors, encara que la majoria dels treballs es centren en la detecció d'una única fallida. Per tant, hi ha una manca de mètodes de diagnòstic capaços de detectar diferents tipus de defectes en un actuador electromecànic. Hi ha molt pocs estudis relacionats amb els sistemes de diagnòstic, capaços d'identificar diverses fallides sota diferents condicions d'operació, i molt menys analitzar profundament tota la cadena de diagnòstic per afrontar el problema des de totes les perspectives possibles. En aquesta tesi, es proposa la investigació sobre tècniques per a la monitorització de condició de sistemes electromecànics, basada en el reconeixement de patrons. Per tal d'identificar diferents fallides sota diferents condicions d'operació, les tècniques propostes s'elaboren sota el prisma de la fusió de dades. El tractament de grans quantitats d'informació, millora els resultats dels algoritmes de reconeixement de patrons, però al seu torn, requereixen de l'aplicació de tècniques i metodologies avançades. Per tant, inicialment es realitza una revisió de la cadena de diagnòstic complerta, incloent les metodologies i tècniques per a les diferents etapes (càlcul d'indicadors, reducció de dimensionalitat i classificació). La revisió finalitza amb la presentació de les estratègies proposades com aportació en cada etapa de diagnòstic. Els resultats obtinguts permeten avenços significatius cap als sistemes de diagnòstic integrals. En aquest sentit, es presenta la investigació sobre metodologies de càlcul d'indicadors en condicions no estacionàries. A continuació, en l'etapa de reducció de dimensionalitat, es proposen metodologies col•laboratives aplicant diferents tècniques que permeten millorar la discriminació de classes, concretament es proposa un enfocament basant-se en tècniques no lineals, que no s'usen habitualment. Finalment, s'analitzen les diferents estructures de classificació i es proposa una arquitectura nova de classificació per ser aplicada en problemes de diagnòstic de múltiples fallides. Es presenten resultats experimentals de les diferents metodologies propostes, per a diferents configuracions electromecàniques. Els resultats obtinguts mostren un alt nivell de rendiment, i les metodologies proposades es poden adaptar als requisits de diagnòstic necessàries en diferents aplicacions. Es conclou que la informació resultant permet una millor comprensió del comportament del sistema sota test, i això té un efecte directe sobre la seva fiabilitat d'operació.
Los accionamientos electromecánicos han tenido tradicionalmente su campo de aplicación en el sector industrial. Sin embargo el uso de este tipo de sistemas se está extendiendo hacia otros sectores dentro del ámbito de los transportes, como el sector del automóvil, o el sector de la aeronáutica con el desarrollo del concepto del Avión Más Eléctrico (MEA). Una de las mejoras más importantes del concepto MEA está relacionada con los actuadores de los controles primarios de vuelo, donde hasta el momento sólo se han considerado actuadores electrohidráulicos, aunque la tendencia actual es remplazarlos por actuadores electromecánicos (EMA). El uso generalizado, en el futuro, de accionamientos EMA en sistemas de transporte, pasa por la investigación y los avances en los algoritmos de detección y diagnóstico de fallos que se puedan producir, tanto en la parte eléctrica como en la mecánica, con el fin de garantizar la fiabilidad del accionamiento y la seguridad de los usuarios. Durante los últimos años, el estudio de sistemas electromecánicos y el diagnóstico de fallos en diversas condiciones de par y de régimen de funcionamiento, han sido estudiados profundamente por diferentes autores, aunque la mayoría de los trabajos se centran en la detección de un único fallo. Por lo tanto, existe una falta de métodos de diagnóstico capaces de detectar diferentes tipos de defectos en un actuador electro-mecánico. Hay muy pocos estudios relacionados con los sistemas de diagnóstico, capaces de identificar diversos fallos bajo diferentes condiciones de operación, y mucho menos analizar profundamente toda la cadena de diagnóstico para afrontar el problema desde todas las perspectivas posibles. En esta tesis, se propone la investigación sobre técnicas para la monitorización de condición de sistemas electromecánicos, basados en el reconocimiento de patrones. Con el fin de identificar diferentes fallos bajo diferentes condiciones de operación, las técnicas propuestas se elaboran bajo el prisma de la fusión de datos. El tratamiento de grandes cantidades de información, mejora los resultados de los algoritmos de reconocimiento de patrones, pero a su vez, requieren de la aplicación de técnicas y metodologías avanzadas. Por lo tanto, inicialmente se realiza una revisión de la cadena de diagnóstico completa, incluyendo las metodologías y técnicas para las diferentes etapas (cálculo de indicadores, reducción de dimensionalidad y clasificación). La revisión finaliza con la presentación de las estrategias propuestas como aportación en cada etapa de diagnóstico. Los resultados obtenidos permiten avances significativos hacia los sistemas de diagnóstico integrales. En este sentido, se presenta la investigación sobre metodologías de cálculo de indicadores en condiciones no estacionarias. A continuación, en la etapa de reducción de dimensionalidad, se proponen metodologías colaborativas aplicando diferentes técnicas que permiten mejorar la discriminación de clases; concretamente se propone un enfoque basándose en técnicas no lineales, que no se usan habitualmente. Finalmente, se analizan las diferentes estructuras de clasificación y se propone una arquitectura novedosa de clasificación para ser aplicada en problemas de diagnóstico de múltiples fallos. Se presentan resultados experimentales de las diferentes metodologías propuestas, para diferentes configuraciones electro-mecánicas. Los resultados obtenidos muestran un alto nivel de rendimiento, y las metodologías propuestas se pueden adaptar a los requisitos de diagnóstico necesarias en diferentes aplicaciones. Se concluye que la información resultante permite una mejor comprensión del comportamiento del sistema bajo test, y esto tiene un efecto directo sobre su fiabilidad de operación.
MacEwen, Clare. "Can data fusion techniques predict adverse physiological events during haemodialysis?" Thesis, University of Oxford, 2016. https://ora.ox.ac.uk/objects/uuid:1ef92d5d-920d-4ff4-b368-5e892527e675.
Full textSKEPPE, LOVISA. "Classify Swedish bank transactions withearly and late fusion techniques." Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-156312.
Full textAtt sköta sin privatekonomi med hjälp av kategorisering gör nog många människor omedvetet, en försöker helt enkelt få en känsla pa vad en lägger sina pengar på. För att kunna ge full översikt på hur ens privatekonomi ser ut, har Tink skapat en mobilapplikation for att automatiskt kategorisera banktransaktioner. Detta görs just nu med klustering och längsta prex matchning på forsäljningsställe. Kategoriseringen av banktransaktioner ger användaren en direkt återkoppling på hur pengaflödet ser ut samt till vad och när dessa köp görs. Den har uppsatsen kommer att undersoka om en maskininlärningsmodell kan lära sig att klassicera banktransaktioner baserat pa köp istället för försäljningsställe. Genom att undersöka två olika fusioneringsscheman på tre typer av modaliteter funna i banktransaktioner (text, pris och datum), ska vi forsoka uttröna dessa modaliteters påverkan på klassicering. De olika scheman är jamförda med ingen fusionering, dvs inlärning på endast en modalitet, och travad klassicering,dvs inlärning med era efterföljande modeller.Experimenten ar gjorda med supervised-learning och inlärningsmodellerna är Naive Bayes, Support Vector Machines samt Beslutstrad. Experimenten visar på att klassicering på text, alltså försäljningsställe ger bäst resultat i jämförelse med alla de andra experimenten. I de tidiga fusionsexperimenten visar alla modalitet-sammanslagningar sämre resultat än ingen fusion på bara text. De sena fusion experimenten visar å andra sidan ingen skillnad alls efter fusionering med modaliteternas pris och datum. Förslag på förbättrad klassicering på köp antas öka, alltså modaliteternas pris och datum bör vara mer betydande, om mer var datamärkt av användare.
Rogowski, Justin. "Investigation into automatic identification of bottlenose dolphins using data fusion techniques." Thesis, University of Derby, 2008. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.506682.
Full textMesina, Justin E. "Urban Classification Techniques Using the Fusion of LiDAR and Spectral Data." Thesis, Monterey, California. Naval Postgraduate School, 2012. http://hdl.handle.net/10945/17420.
Full textCombining different types of data from varying sensors has the potential to be more accurate than a single sensor. This research fused airborne LiDAR data and WorldView-2 (WV-2) multispectral imagery (MSI) data to create an improved classification image of urban San Francisco, California. A decision tree scenario was created by extracting features from the LiDAR, as well as NDVI from the multispectral data. Raster masks were created using these features and were processed as decision tree nodes resulting in seven classifications. Twelve regions of interest were created, then categorized and applied to the previous seven classifications via the maximum likelihood classification. The resulting classification images were then combined. A multispectral classification image using the same ROIs was also created for comparison. The fused classification image did a better job of preserving urban geometries than MSI data alone and suffered less from shadow anomalies. The fused results however, were not as accurate in differentiating trees from grasses as using only spectral results. Overall the fused LiDAR and MSI classification performed better than the MSI classification alone but further refinements to the decision tree scheme could probably be made to improve final results.
De, Gregorio Ludovica. "Development of new data fusion techniques for improving snow parameters estimation." Doctoral thesis, Università degli studi di Trento, 2019. http://hdl.handle.net/11572/245392.
Full textAdusumilli, Srujana. "Development of Statistical Learning Techniques for INS and GPS Data Fusion." University of Toledo / OhioLINK, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1398772813.
Full textKwon, Samuel M. (Samuel Moonha). "Pixel-level data fusion techniques applied to the detection of gust fonts." Thesis, Massachusetts Institute of Technology, 1994. http://hdl.handle.net/1721.1/38351.
Full textJarrell, Jason A. "Employ sensor fusion techniques for determining aircraft attitude and position information." Morgantown, W. Va. : [West Virginia University Libraries], 2008. https://eidr.wvu.edu/etd/documentdata.eTD?documentid=5894.
Full textTitle from document title page. Document formatted into pages; contains xii, 108, [9] p. : ill. (some col.). Includes abstract. Includes bibliographical references (p. 104-108).
Rajan, Krithika. "Analysis of pavement condition data employing Principal Component Analysis and sensor fusion techniques." Thesis, Manhattan, Kan. : Kansas State University, 2008. http://hdl.handle.net/2097/873.
Full textLiu, Xiaofeng. "Machinery fault diagnostics based on fuzzy measure and fuzzy integral data fusion techniques." Thesis, Queensland University of Technology, 2007. https://eprints.qut.edu.au/16456/1/Xiaofeng_Liu_Thesis.pdf.
Full textLiu, Xiaofeng. "Machinery fault diagnostics based on fuzzy measure and fuzzy integral data fusion techniques." Queensland University of Technology, 2007. http://eprints.qut.edu.au/16456/.
Full textOthman, Nadia. "Fusion techniques for iris recognition in degraded sequences." Thesis, Université Paris-Saclay (ComUE), 2016. http://www.theses.fr/2016SACLL003/document.
Full textAmong the large number of biometric modalities, iris is considered as a very reliable biometrics with a remarkably low error rate. The excellent performance of iris recognition systems are obtained by controlling the quality of the captured images and by imposing certain constraints on users, such as standing at a close fixed distance from the camera. However, in many real-world applications such as control access and airport boarding these constraints are no longer suitable. In such non ideal conditions, the resulting iris images suffer from diverse degradations which have a negative impact on the recognition rate. One way to try to circumvent this bad situation is to use some redundancy arising from the availability of several images of the same eye in the recorded sequence. Therefore, this thesis focuses on how to fuse the information available in the sequence in order to improve the performance. In the literature, diverse schemes of fusion have been proposed. However, they agree on the fact that the quality of the used images in the fusion process is an important factor for its success in increasing the recognition rate. Therefore, researchers concentrated their efforts in the estimation of image quality to weight each image in the fusion process according to its quality. There are various iris quality factors to be considered and diverse methods have been proposed for quantifying these criteria. These quality measures are generally combined to one unique value: a global quality. However, there is no universal combination scheme to do so and some a priori knowledge has to be inserted, which is not a trivial task. To deal with these drawbacks, in this thesis we propose of a novel way of measuring and integrating quality measures in a super-resolution approach, aiming at improving the performance. This strategy can handle two types of issues for iris recognition: the lack of resolution and the presence of various artifacts in the captured iris images. The first part of the doctoral work consists in elaborating a relevant quality metric able to quantify locally the quality of the iris images. Our measure relies on a Gaussian Mixture Model estimation of clean iris texture distribution. The interest of our quality measure is 1) its simplicity, 2) its computation does not require identifying in advance the type of degradations that can occur in the iris image, 3) its uniqueness, avoiding thus the computation of several quality metrics and associated combination rule and 4) its ability to measure the intrinsic quality and to specially detect segmentation errors. In the second part of the thesis, we propose two novel quality-based fusion schemes. Firstly, we suggest using our quality metric as a global measure in the fusion process in two ways: as a selection tool for detecting the best images and as a weighting factor at the pixel-level in the super-resolution scheme. In the last case, the contribution of each image of the sequence in final fused image will only depend on its overall quality. Secondly, taking advantage of the localness of our quality measure, we propose an original fusion scheme based on a local weighting at the pixel-level, allowing us to take into account the fact that degradations can be different in diverse parts of the iris image. This means that regions free from occlusions will contribute more in the image reconstruction than regions with artefacts. Thus, the quality of the fused image will be optimized in order to improve the performance. The effectiveness of the proposed approaches is shown on several databases commonly used: MBGC, Casia-Iris-Thousand and QFIRE at three different distances: 5, 7 and 11 feet. We separately investigate the improvement brought by the super-resolution, the global quality and the local quality in the fusion process. In particular, the results show the important improvement brought by the use of the global quality, improvement that is even increased using the local quality
Van, Huyssteen David. "Application of sensor data fusion techniques to the light armoured vehicle reconnaissance (LAV Recce)." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1998. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape11/PQDD_0002/MQ44861.pdf.
Full textVILLANUEVA, JUAN MOISES MAURICIO. "DATA FUSION OF TIME OF FLIGHT TECHNIQUES USING ULTRASONIC TRANSDUCERS FOR WIND SPEED MEASUREMENT." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2009. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=32625@1.
Full textCOORDENAÇÃO DE APERFEIÇOAMENTO DO PESSOAL DE ENSINO SUPERIOR
CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO
PROGRAMA DE EXCELENCIA ACADEMICA
A medição da velocidade de fluidos tem relevância considerável em aplicações industriais e científicas, nas quais medições com baixa incerteza são geralmente requeridas. Nesta tese, tem-se como objetivo projetar e modelar um sistema de medição de velocidade de vento utilizando fusão de dados das informações dos tempos de trânsito obtidas pelas técnicas de detecção de limiar e diferença de fase. Para este propósito, este trabalho é composto por duas partes principais. Na primeira parte, apresenta-se uma análise da propagação de incertezas das técnicas de detecção de limiar e diferença de fase considerando duas estruturas para a medição da velocidade do vento, e faz-se a comparação das faixas de medição e suas incertezas associadas para cada estrutura de medição. Na segunda parte deste trabalho, faz-se um estudo das técnicas de fusão de dados aplicadas a instrumentação e medição, identificandose duas técnicas principais baseadas em: (a) estimação de máxima probabilidade (MLE – Maximum Likelihood Estimation), (b) relação de compatibilidade fuzzy e operadores OWA (Order Weighted Average) com agregação parcial. Em seguida, estas técnicas de fusão são aplicadas para a estimação do tempo de trânsito, considerando-se várias medições independentes do tempo de trânsito obtidas pelas técnicas de detecção de limiar e diferença de fase. Finalmente, realiza-se uma análise da incerteza quantificando-se a incerteza de cada medição sobre o resultado final de fusão. Apresenta-se um estudo de caso englobando estas duas partes do trabalho, desenvolvendo-se o projeto e modelagem de um instrumento de medição de velocidade do vento com baixa incerteza, considerando-se as incertezas associadas, e o uso de técnicas adequadas de fusão de dados para prover informações com maior exatidão e confiabilidade. Resultados experimentais são realizados em um túnel de vento de baixa velocidade com o objetivo de verificar a consistência dos estudos teóricos apresentados.
Flow speed measurement has considerable relevance in industrial and scientific applications, where measurements with low uncertainty are required. In this work, a system for wind speed measurement using ultrasonic transducers is designed and modelled. This system makes use of data fusion techniques for the time-of-flight estimation, combining independent information provided by the threshold detection and phase difference methods. For this purpose, this work consists of two main parts. The first part presents an analysis of uncertainty and error propagation concerning the threshold detection and phase difference techniques and considering two structures for the wind speed measurement. Measurement ranges are associated uncertainties are then compared for each of those estrutures. In the second part of this work, data fusion techniques applied to instrumentation and measurement are studied; two main techniques are singled out: (a) Maximum Likelihood Estimation (MLE), (b) Fuzzy compatibility relation and Order Weighted Average (OWA) operators with partial aggregation. These fusion techniques are then applied to the time-of-flight estimation, by considering several independent measurements obtained through the threshold detection and phase difference techniques. Finally, uncertainty analysis is carried out by quantifying the influence of each independent measurement on the global fusion result. A case study is also presented, where an instrument for wind speed measurements with low uncertainty is designed and modelled. Appropriate techniques of data fusion aimed at improving accuracy and realiability are considered. Experiments are performed in a wind tunnel in order to verify the consistency of the results in view of the theoretical studies.
Engebretson, Kent Russell. "A comparison of data fusion techniques for target detetction with a wide azimuth sonar." Thesis, Massachusetts Institute of Technology, 1995. http://hdl.handle.net/1721.1/39367.
Full textIncludes bibliographical references (p. 133).
by Kent Russell Engebretson.
M.S.
Miranda, Luís Miguel Gonçalves. "Data fusion with computational intelligence techniques: a case study of fuzzy inference for terrain assessment." Master's thesis, Faculdade de Ciências e Tecnologia, 2014. http://hdl.handle.net/10362/12338.
Full textWith the constant technology progression is inherent storage of all kinds of data. Satellites, mobile phones, cameras and other type of electronic equipment, produce on daily basis an amount of data of gigantic proportions. These data alone may not convey any meaning and may even be impossible to interpret them without specific auxiliary measures. Data fusion contributes in this issue giving use of these data, processing them into proper knowledge for whom analyzes. Within data fusion there are numerous processing approaches and methodologies, being given here highlight to the one that most resembles to the imprecise human knowledge, the fuzzy reasoning. These method is applied in several areas, inclusively as inference system for hazard detection and avoidance in unmanned space missions. To this is fundamental the use of fuzzy inference systems, where the problem is modeled through a set of linguistic rules, fuzzy sets, membership functions and other information. In this thesis it was developed a fuzzy inference system, for safe landing sites using fusion of maps, and a data visualization tool. Thus, classification and validation of the information are made easier with such tools.
Wragge-Morley, Robert. "Parameter estimation in road vehicles using non-linear adaptive observer and novel data fusion techniques." Thesis, University of Bristol, 2017. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.715766.
Full textLandberg, Markus. "Enhancement Techniques for Lane PositionAdaptation (Estimation) using GPS- and Map Data." Thesis, Linköpings universitet, Datorseende, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-110812.
Full textEtt filpositioneringssystem undersöks och förbättringstekniker för ökandet av robusthetoch tillgängligheten av ett sådant system genom att använda ytterligaresensorkällor som kartdata och GPS. Detta examensarbete presenterar beskrivningenav ett system, två modeller och två implementerade filter. Examensarbetetinnehåller också slutsatser och resultat av teoretiska och experimentella testersom plottar och grafer av ökad robusthet och tillgängligheten av systemet. Dettasystem kan bli integrerat med ett framtaget system som tittar på körrelaterat beteendevid trötthet. Systemet är utvecklat i ett projekt kallat Drowsi, där blandandra Volvo Technology deltog.
Kurebayashi, Shinya 1976. "Using Nuclear data and Monte-Carlo techniques to study areal density and mix in D² inertial confinement fusion implosions." Thesis, Massachusetts Institute of Technology, 2004. http://hdl.handle.net/1721.1/29369.
Full textIncludes bibliographical references.
Measurements from three classes of direct-drive implosions at the OMEGA laser system [T. R. Boehly et al., Opt. Commun. 133, 495 (1997)] were combined with Monte-Carlo simulations to investigate models for determining hot-fuel areal density ([rho]Rhot) in compressed, D2-filled capsules, and to assess the impact of mix and other factors on the determination of pRhot. The results of the Monte-Carlo calculations were compared to predictions of commonly used models that use ratios of either secondary D3He proton yields or secondary DT neutron yields to primary DD neutron yields to provide estimates [rho]Rhot or [rho]Rhot,n, respectively, for pRhot. For the first class of implosions, where [rho]Rhot is low (=/< 3 mg/cm2), [rho]Rhot,p and [rho]Rhot,n often agree with each other and are often good estimates of the actual [rho]Rhot. For the second class of implosions, where [rho]Rhot is of order 10 mg/cm2, pRhot,p often underestimates the actual value due to secondary proton yield saturation. In addition, fuel-shell mix causes pRhot,p to further underestimate, and [Rho]Rhot,n to overestimate, [rho]Rhot. As a result, values of [Rho]Rhot,p and [Rho]Rhot,n can be interpreted as lower and upper limits, respectively. For the third class of implosions, involving cryogenic capsules, secondary protons and neutrons are produced mainly in the hot and cold fuel regions, respectively, and the effects of the mixing of hot and cold fuel must be taken into account when interpreting the values of [rho]Rhot,p and pRhot,n. From these data sets, we conclude that accurate inference of [rho]Rhot requires comprehensive measurements in combination with detailed modeling.
by Shinya Kurebayashi.
S.M.
Radhakrishnan, Aswathnarayan. "A Study on Applying Learning Techniques to Remote Sensing Data." The Ohio State University, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=osu1586901481703797.
Full textNicolini, Andrea. "Multipath tracking techniques for millimeter wave communications." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2019. http://amslaurea.unibo.it/17690/.
Full textTopalis, Apostolos. "Multiresolution wavelet analysis of event-related EEG potentials using ensemble of classifier data fusion techniques for early diagnosis of Alzheimer's disease /." Full text available online, 2006. http://www.lib.rowan.edu/find/theses.
Full textKönig, Rikard. "Predictive Techniques and Methods for Decision Support in Situations with Poor Data Quality." Licentiate thesis, Högskolan i Borås, Institutionen Handels- och IT-högskolan, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:hb:diva-3517.
Full textSponsorship:
This work was supported by the Information Fusion Research
Program (www.infofusion.se) at the University of Skövde, Sweden, in
partnership with the Swedish Knowledge Foundation under grant
2003/0104.
Nguyen, Tien Dung. "Multimodal emotion recognition using deep learning techniques." Thesis, Queensland University of Technology, 2020. https://eprints.qut.edu.au/180753/1/Tien%20Dung_Nguyen_Thesis.pdf.
Full textJdey, Aloui Imen. "Contribution des techniques de fusion et de classification des images au processus d'aide à la reconnaissance des cibles radar non coopératives." Thesis, Brest, 2014. http://www.theses.fr/2014BRES0008.
Full textThe automatic recognition of non-cooperative targets is very important in various fields. This is the case for applications in aviation and maritime uncertain environment. Therefore, it’s necessary to introduce innovative methods for radar targets treatment and identification.The proposed methodology is based on the Knowledge Discovery from Data process (KDD) for a complete chain development of radar images recognition by trying to optimize every step of the processing chain.The experimental system used is based on an ISAR image acquisition system in the anechoic chamber of ENSTA Bretagne. This system has allowed controlling the quality of the entries in the recognition process (KDD). We studied the stages of the composite system from acquisition to interpretation and evaluation of results. We focused on the center stage; data mining considered as the heart of the system. This step is composed of two main phases: classification and the results of classifiers combination called decisional fusion. We have shown that this last phase improves results for decision making by taking into account the imperfections related to radar data, including uncertainty and imprecision.The results across different classification techniques as a first step (kNN, SVM and MCP) and decision fusion in a second time (Bayes, majority vote, belief theory, fuzzy fusion) are subject of an analytical and comparative study in terms of performance
Tsenoglou, Theocharis. "Intelligent pattern recognition techniques for photo-realistic 3D modeling of urban planning objects." Thesis, Limoges, 2014. http://www.theses.fr/2014LIMO0075.
Full textRealistic 3D modeling of buildings and other urban planning objects is an active research area in the field of 3D city modeling, heritage documentation, virtual touring, urban planning, architectural design and computer gaming. The creation of such models, very often, requires merging of data from diverse sources such as optical images and laser scan point clouds. To imitate as realistically as possible the layouts, activities and functionalities of a real-world environment, these models need to attain high photo-realistic quality and accuracy in terms of the surface texture (e.g. stone or brick walls) and morphology (e.g. windows and doors) of the actual objects. Image-based rendering is an alternative for meeting these requirements. It uses photos, taken either from ground level or from the air, to add texture to the 3D model thus adding photo-realism. For full texture covering of large facades of 3D block models, images picturing the same façade need to be properly combined and correctly aligned with the side of the block. The pictures need to be merged appropriately so that the result does not present discontinuities, abrupt variations in lighting or gaps. Because these images were taken, in general, under various viewing conditions (viewing angles, zoom factors etc) they are under different perspective distortions, scaling, brightness, contrast and color shadings, they need to be corrected or adjusted. This process requires the extraction of key features from their visual content of images. The aim of the proposed work is to develop methods based on computer vision and pattern recognition techniques in order to assist this process. In particular, we propose a method for extracting implicit lines from poor quality images of buildings, including night views where only some lit windows are visible, in order to specify bundles of 3D parallel lines and their corresponding vanishing points. Then, based on this information, one can achieve better merging of the images and better alignment of the images to the block façades. Another important application dealt in this thesis is that of 3D modeling. We propose an edge preserving interpolation, based on the mean shift algorithm, that operates jointly on the optical and the elevation data. It succeeds in increasing the resolution of the elevation data (LiDAR) while improving the quality (i.e. straightness) of their edges. At the same time, the color homogeneity of the corresponding imagery is also improved. The reduction of color artifacts in the optical data and the improvement in the spatial resolution of elevation data results in more accurate 3D building models. Finally, in the problem of building detection, the application of the proposed mean shift-based edge preserving smoothing for increasing the quality of aerial/color images improves the performance of binary building vs non-building pixel classification
Garcia, garcia Miguel. "Analyse de l'hypovigilance au volant par fusion d'informations environnementales et d'indices vidéo." Thesis, Université Grenoble Alpes (ComUE), 2018. http://www.theses.fr/2018GREAT120.
Full textDriver hypovigilance (whether caused by distraction or drowsiness) is one of the major threats to road safety. This thesis is part of the Toucango project, hold by the start-up Innov+, which aims to build a real-time hypovigilance detector based on the fusion of near infra-red video evidence and environmental information. The objective of this thesis is therefore to propose techniques for extracting relevant indices as well as multimodal fusion algorithms that can be embedded in the system for real-time operation. In order to work near ground truth conditions, a naturalistic driving database has been created with the collaboration of several transport companies. We first present a scientific state of the art and a study of the solutions available on the market for hypovigilance detection. Then, we propose several methods based on image (for the detection of relevant indices on the head, eyes, mouth and face) and data processing (for environmental indices based on geolocation). We carry out a study on the environmental factors related to hypovigilance and develop a contextual risk estimation system. Finally, we propose multimodal fusion techniques of these indices with the objective of detecting several hypovigilance behaviors: visual or cognitive distraction, engagement in a secondary task, sleep deprivation, microsleep and drowsiness
Hammami, Imen. "Fusion d'images de télédétection hétérogènes par méthodes crédibilistes." Thesis, Ecole nationale supérieure Mines-Télécom Atlantique Bretagne Pays de la Loire, 2017. http://www.theses.fr/2017IMTA0034/document.
Full textWith the advent of new image acquisition techniques and the emergence of high-resolution satellite systems, remote sensing data to be exploited have become increasingly rich and varied. Their combination has thus become essential to improve the process of extracting useful information related to the physical nature of the observed surfaces. However, these data are generally heterogeneous and imperfect, which poses several problems in their joint treatment and requires the development of specific methods. It is in this context that falls this thesis that aimed at developing a new evidential fusion method dedicated to heterogeneous remote sensing images processing at high resolution. In order to achieve this objective, we first focus our research, firstly, on the development of a new approach for the belief functions estimation based on Kohonen’s map in order to simplify the masses assignment operation of the large volumes of data occupied by these images. The proposed method allows to model not only the ignorance and the imprecision of our sources of information, but also their paradox. After that, we exploit this estimation approach to propose an original fusion technique that will solve problems due to the wide variety of knowledge provided by these heterogeneous sensors. Finally, we study the way in which the dependence between these sources can be considered in the fusion process using the copula theory. For this reason, a new technique for choosing the most appropriate copula is introduced. The experimental part of this work isdevoted to land use mapping in case of agricultural areas using SPOT-5 and RADARSAT-2 images. The experimental study carried out demonstrates the robustness and effectiveness of the approaches developed in the framework of this thesis
Wang, Xiaoguang. "Design and Analysis of Techniques for Multiple-Instance Learning in the Presence of Balanced and Skewed Class Distributions." Thesis, Université d'Ottawa / University of Ottawa, 2015. http://hdl.handle.net/10393/32184.
Full textParshyn, Viachaslau. "Macro-segmentation sémantique des séquences multimédia." Ecully, Ecole centrale de Lyon, 2006. http://bibli.ec-lyon.fr/exl-doc/vparshyn.pdf.
Full textSegmentation of video into temporal semantic units provides important indexing information for efficient content-based browsing and navigation. In this work we are concerned withe the problem of macro-segmentation aiming at automatic generating of content tables of videos. We propose a deterministic approach which is a sort of finite automation and allows one to formulate content parsing rules based on a priori knowledge of the video production principles. The approach has been adopted und tested on tennis video. We propose also a statistical segmentation framework where content parsing rules are chosen so as to optimize the system performance measured as recall and precision. The framework is applied to the task of film segmentation into semantic scenes. The higher segmentation performance has been shown with respect to conventional rule-based ans statistical methods. In this work we are also concerned with the problem of automatic video summarization
Lian, Chunfeng. "Information fusion and decision-making using belief functions : application to therapeutic monitoring of cancer." Thesis, Compiègne, 2017. http://www.theses.fr/2017COMP2333/document.
Full textRadiation therapy is one of the most principal options used in the treatment of malignant tumors. To enhance its effectiveness, two critical issues should be carefully dealt with, i.e., reliably predicting therapy outcomes to adapt undergoing treatment planning for individual patients, and accurately segmenting tumor volumes to maximize radiation delivery in tumor tissues while minimize side effects in adjacent organs at risk. Positron emission tomography with radioactive tracer fluorine-18 fluorodeoxyglucose (FDG-PET) can noninvasively provide significant information of the functional activities of tumor cells. In this thesis, the goal of our study consists of two parts: 1) to propose reliable therapy outcome prediction system using primarily features extracted from FDG-PET images; 2) to propose automatic and accurate algorithms for tumor segmentation in PET and PET-CT images. The theory of belief functions is adopted in our study to model and reason with uncertain and imprecise knowledge quantified from noisy and blurring PET images. In the framework of belief functions, a sparse feature selection method and a low-rank metric learning method are proposed to improve the classification accuracy of the evidential K-nearest neighbor classifier learnt by high-dimensional data that contain unreliable features. Based on the above two theoretical studies, a robust prediction system is then proposed, in which the small-sized and imbalanced nature of clinical data is effectively tackled. To automatically delineate tumors in PET images, an unsupervised 3-D segmentation based on evidential clustering using the theory of belief functions and spatial information is proposed. This mono-modality segmentation method is then extended to co-segment tumor in PET-CT images, considering that these two distinct modalities contain complementary information to further improve the accuracy. All proposed methods have been performed on clinical data, giving better results comparing to the state of the art ones
Pellicanò, Nicola. "Tackling pedestrian detection in large scenes with multiple views and representations." Thesis, Université Paris-Saclay (ComUE), 2018. http://www.theses.fr/2018SACLS608/document.
Full textPedestrian detection and tracking have become important fields in Computer Vision research, due to their implications for many applications, e.g. surveillance, autonomous cars, robotics. Pedestrian detection in high density crowds is a natural extension of such research body. The ability to track each pedestrian independently in a dense crowd has multiple applications: study of human social behavior under high densities; detection of anomalies; large event infrastructure planning. On the other hand, high density crowds introduce novel problems to the detection task. First, clutter and occlusion problems are taken to the extreme, so that only heads are visible, and they are not easily separable from the moving background. Second, heads are usually small (they have a diameter of typically less than ten pixels) and with little or no textures. This comes out from two independent constraints, the need of one camera to have a field of view as high as possible, and the need of anonymization, i.e. the pedestrians must be not identifiable because of privacy concerns.In this work we develop a complete framework in order to handle the pedestrian detection and tracking problems under the presence of the novel difficulties that they introduce, by using multiple cameras, in order to implicitly handle the high occlusion issues.As a first contribution, we propose a robust method for camera pose estimation in surveillance environments. We handle problems as high distances between cameras, large perspective variations, and scarcity of matching information, by exploiting an entire video stream to perform the calibration, in such a way that it exhibits fast convergence to a good solution. Moreover, we are concerned not only with a global fitness of the solution, but also with reaching low local errors.As a second contribution, we propose an unsupervised multiple camera detection method which exploits the visual consistency of pixels between multiple views in order to estimate the presence of a pedestrian. After a fully automatic metric registration of the scene, one is capable of jointly estimating the presence of a pedestrian and its height, allowing for the projection of detections on a common ground plane, and thus allowing for 3D tracking, which can be much more robust with respect to image space based tracking.In the third part, we study different methods in order to perform supervised pedestrian detection on single views. Specifically, we aim to build a dense pedestrian segmentation of the scene starting from spatially imprecise labeling of data, i.e. heads centers instead of full head contours, since their extraction is unfeasible in a dense crowd. Most notably, deep architectures for semantic segmentation are studied and adapted to the problem of small head detection in cluttered environments.As last but not least contribution, we propose a novel framework in order to perform efficient information fusion in 2D spaces. The final aim is to perform multiple sensor fusion (supervised detectors on each view, and an unsupervised detector on multiple views) at ground plane level, that is, thus, our discernment frame. Since the space complexity of such discernment frame is very large, we propose an efficient compound hypothesis representation which has been shown to be invariant to the scale of the search space. Through such representation, we are capable of defining efficient basic operators and combination rules of Belief Function Theory. Furthermore, we propose a complementary graph based description of the relationships between compound hypotheses (i.e. intersections and inclusion), in order to perform efficient algorithms for, e.g. high level decision making.Finally, we demonstrate our information fusion approach both at a spatial level, i.e. between detectors of different natures, and at a temporal level, by performing evidential tracking of pedestrians on real large scale scenes in sparse and dense conditions
Hannachi, Ammar. "Imagerie multimodale et planification interactive pour la reconstruction 3D et la métrologie dimensionnelle." Thesis, Strasbourg, 2015. http://www.theses.fr/2015STRAD024/document.
Full textProducing industrially manufactured parts generates a very large number of data of various types defining the manufacturing geometries as well as the quality of production. This PhD work has been carried out within the framework of the realization of a cognitive vision system dedicated to the 3D evaluation of manufactured objects including possibly free form surfaces, taking into account the geometric tolerances and uncertainties. This system allows the comprehensive control of manufactured parts, and provides the means for their automated 3D dimensional inspection. The implementation of a multi-sensor (passive and active) measuring system enabled to improve significantly the assessment quality through an enriched three-dimensional reconstruction of the object to be evaluated. Specifically, we made use simultaneously of a stereoscopic vision system and of a structured light based system in order to reconstruct the edges and surfaces of various 3D objects
Buckley, Simon John. "A geomatics data fusion technique for change monitoring." Thesis, University of Newcastle Upon Tyne, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.405351.
Full textBertrand, Sarah. "Analyse d'images pour l'identification multi-organes d'espèces végétales." Thesis, Lyon, 2018. http://www.theses.fr/2018LYSE2127/document.
Full textThis thesis is part of the ANR ReVeRIES, which aims to use mobile technologies to help people better understand their environment and in particular the plants that surround them. More precisely, the ReVeRIES project is based on a mobile application called Folia developed as part of the ANR ReVeS project and capable of recognising tree and shrub species based on photos of their leaves. This prototype differs from other tools in that it is able to simulate the behaviour of the botanist. In the context of the ReVeRIES project, we propose to go much further by developing new aspects: multimodal species recognition, learning through play and citizen science. The purpose of this thesis is to focus on the first of these three aspects, namelythe analysis of images of plant organs for identification.More precisely, we consider the main trees and shrubs, endemic or exotic, found in metropolitan France. The objective of this thesis is to extend the recognition algorithm by taking into account other organs in addition to the leaf. This multi-modality is indeed essential if we want the user to learn and practice the different methods of recognition for which botanists use the variety of organs (i.e. leaves, flowers, fruits and bark). The method used by Folia for leaf recognition being dedicated, because simulating the work of a botanist on the leaf, cannot be applied directly to other organs. Thus, new challenges are emerging, both in terms of image processing and data fusion.The first part of the thesis was devoted to the implementation of image processing methods for the identification of plant species. The identification of tree species from bark images was the first to be studied. The descriptors developed take into account the structure of the bark inspired from the criteria used by botanists. Fruits and flowers required a segmentation step before their description. A new segmentation method that can be used on smartphones has been developed to work in spite of the high variability of flowers and fruits. Finally, descriptors were extracted on fruits and flowers after the segmentation step. We decided not to separate flowers and fruits because we showed that a user new to botany does not always know the difference between these two organs on so-called "ornamental" trees (not fruit trees). For fruits and flowers, prediction is not only made on their species but also on their genus and family, botanical groups reflecting a similarity between these organs.The second part of the thesis deals with the combination of descriptors of the different organs: leaves, bark, fruits and flowers. In addition to basic combination methods, we propose to consider the confusion between species, as well as predictions of affiliations in botanical taxa higher than the species.Finally, an opening chapter is devoted to the processing of these images by convolutional neural networks. Indeed, Deep Learning is increasingly used in image processing, particularly for plant organs. In this context, we propose to visualize the learned convolution filters extracting information, in order to make the link between the information extracted by these networks and botanical elements
Vannah, Benjamin. "Integrated Data Fusion and Mining (IDFM) Technique for Monitoring Water Quality in Large and Small Lakes." Master's thesis, University of Central Florida, 2013. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/6028.
Full textM.S.Env.E.
Masters
Civil, Environmental and, Construction Engineering
Engineering and Computer Science
Environmental Engineering
Vivet, Damien. "Perception de l'environnement par radar hyperfréquence. Application à la localisation et la cartographie simultanées, à la détection et au suivi d'objets mobiles en milieu extérieur." Phd thesis, Université Blaise Pascal - Clermont-Ferrand II, 2011. http://tel.archives-ouvertes.fr/tel-00659270.
Full textHarizi, Walid. "Caractérisation de l'endommagement des composites à matrice polymère par une approche multi-technique non destructive." Thesis, Valenciennes, 2012. http://www.theses.fr/2012VALE0033.
Full textThis innovative study consists to implement in the same experimental procedure three non destructive techniques simultaneously: acoustic emission, infrared thermography and ultrasonic waves for the characterization of damage in cross ply Polymer Composite Materials (PCM) [0/90]S. Each technique has demonstrated its potential to reveal the damage that depends on its intrinsic characteristics. Acoustic emission has been used in its classical form and coupled with a data classification obtained by k-means and Kohonen map. Infrared thermography has been studied using both passive and active forms, ultrasonic methods have been used by exploiting amplitude and velocity of longitudinal and Lamb waves respectively. It has been shown that the adopted multi-technique approach is veryinteresting to obtain a full diagnostic of the health state of the material before and after uniaxial mechanical loading. The “complementarity” aspect between the three used techniques is showed more interesting that “redundancy” aspect. The data fusion theory was used to have a reliable, comprehensive and credible decision about the different damage mechanisms may appear in PCM material. This has been possible only for the two imaging techniques, ultrasonic C-scan and infrared thermography. All in all, the results show that these three techniques are potentially able to describe the damage state of the material, but they don’t quantify it with the same manner
Reche, Jérôme. "Nouvelle méthodologie hybride pour la mesure de rugosités sub-nanométriques." Thesis, Université Grenoble Alpes (ComUE), 2019. http://www.theses.fr/2019GREAT050.
Full textRoughness at Sub-nanometric scale determination becomes a critical issue, especially for patterns with critical dimensions below 10nm. Currently, there is no metrology technique able to provide a result with high precision and accuracy. A way, based on hybrid metrology, is currently explored and dedicated to dimensional measurements. This hybrid metrology uses data fusion algorithms in order to address data coming from different tools. This thesis presents some improvements on line roughness analysis thanks to frequency decomposition and associated model. The current techniques used for roughness determination are explained and a new one SAXS (Small Angle X-rays Scattering) is used to push again limits of extraction of roughness. This technique has a high potential to determine sub nanometrics patterns. Moreover, the design and manufacturing of reference line roughness samples is made, following the state of art with periodic roughness, but also more complex roughness determined by a statistical model usually used for measurement. Finally, this work focus on hybridization methods and more especially on neural network utilization. Thus, the establishment of a neural network is detailed through the multitude of parameters which must be set. In addition, training of the neural network on simulation leads to the capability to generate different metrology
Griesbach, schuch Nivea. "Métrologie Hybride pour le contrôle dimensionnel en lithographie." Thesis, Université Grenoble Alpes (ComUE), 2017. http://www.theses.fr/2017GREAT063/document.
Full textThe industry of semiconductors continues to evolve at a fast pace, proposing a new technology node around every two years. Each new technology node presents reduced feature sizes and stricter dimension control. As the features of devices continue to shrink, allowed tolerances for metrology errors must shrink as well, pushing the evolution of the metrology tools.No individual metrology technique alone can answer the tight requirements of the industry today, not to mention in the next technology generations. Besides the limitations of the metrology methods, other constraints such as the amount of metrology data available for higher order analysis and the time required for generating such data are also relevant and impact the usage of metrology in production. For the production of advanced technology nodes, neither speed nor precision may be sacrificed, which calls for cleverer metrology approaches, such as the Hybrid Metrology.Hybrid Metrology consists of employing different metrology strategies together in order to combine their strengths while mitigating their weaknesses. This hybrid approach goal is to improve the measurements in such a way that the final data presents better characteristics that each method separately. One of the techniques than can be used to combine the data coming from different metrology techniques is called Data Fusion. There are a large number of developed methods of Data Fusion, using different mathematical tools, to address the data fusion process.The first goal of this thesis project was to start developing the topics of Data Fusion and Hybrid Metrology within the two laboratories whose cooperation made this work possible: LTM (Laboratoire des Technologies de la Microélectronique) and LETI (Laboratoire d'électronique et de technologie de l'information). This thesis presents the concepts of Data Fusion in the context of Hybrid Metrology applied to dimensional measuring for the semiconductors industry. This concept can be extensively used in many other fields of applications.In this work the basics of state-of-the-art metrology techniques is presented and discussed. The focus is the CD-SEM, for its fast and almost-non-destructive metrology; the AFM, for its accurate profile view of patterns and non-destructive characteristic; the Scatterometry, for its precision, global and fast measurements; and the FIB-STEM, as a reference on accuracy for any type of profile, although destructive. The strengths and weaknesses of these methods were discussed in order to introduce the need of Hybrid Metrology and to identify the role that each of those methods can play in this context.Several experiments were performed during this thesis work in order to provide further knowledge about the characteristics and limitations of each metrology method and to be used as either inputs or reference on the different Hybrid Metrology scenarios proposed.The selected method for fuse the data coming from different metrology methods was the Bayesian approach. This technique was evaluated in different experimental contexts, both for Height and CD metrology combining different metrology methods. Results were evaluated for both the debiasing step alone and for the complete fusion flow. In both cases, it was clear the advantages of using a Hybrid Metrology approach for improving the measurement precision and accuracy.The presented Hybrid Metrology technique may be used by the semiconductor industry in different steps of the fabrication process. This technique can also provide information for machine calibration, such as a CD-SEM tool being calibrated based on Hybrid Metrology results generated using the CD-SEM itself together with Scatterometry data
Elshehaly, Mai, D. Gračanin, M. Gad, H. G. Elmongui, and K. Matković. "Interactive Fusion and Tracking For Multi‐Modal Spatial Data Visualization." 2015. http://hdl.handle.net/10454/17884.
Full textScientific data acquired through sensors which monitor natural phenomena, as well as simulation data that imitate time‐identified events, have fueled the need for interactive techniques to successfully analyze and understand trends and patterns across space and time. We present a novel interactive visualization technique that fuses ground truth measurements with simulation results in real‐time to support the continuous tracking and analysis of spatiotemporal patterns. We start by constructing a reference model which densely represents the expected temporal behavior, and then use GPU parallelism to advect measurements on the model and track their location at any given point in time. Our results show that users can interactively fill the spatio‐temporal gaps in real world observations, and generate animations that accurately describe physical phenomena.
Shun, Hsueh Chi, and 薛吉順. "Multisernsor Data Fusion Techniques for Robotic Control in Military Applications." Thesis, 1999. http://ndltd.ncl.edu.tw/handle/25408018477637986448.
Full text中正理工學院
兵器系統工程研究所
87
Single sensor perceptual systems in robot has not been entirely successful for more demanding tasks in navigation, tracking and goal recognition. This has limited the potential benefits of robots for applications in space, defense, and manufacturing. Multisensor data fusion (MSDF) is being increasingly viewed as an important perceptual activity in robotics. The use of sensory data from a range of disparate, multiple sensors is to automatically extract the maximum amount of information possible about the sensed environment under all operating conditions. In the first part of this thesis we show the results of the implementation of the neural networks (NN) tracking controller on a SCORBOT ER VII manipulator. The NN feed-forward controller was employed in the first one control scheme, which is composed of a feedback proportional derivative (PD) controller. In the second control scheme, a new NN was incorporated for augmenting the first scheme in order to compensate the trajectory planner. It is shown that the tracking performance of the dual NN with PD controller is far better than that of the PD standard controller or NN with PD feed-forward/feedback controllers. In the second part of this thesis we employed an Elman neural network as sensory data fusion computational technique for approximation of the visual/servo (camera/joints) optimal mapping. The results showed that the network can successfully predict the next position of the tracking target. The new approach applied on a learning predictive controller for the SCORBOT ER VII robot manipulator has successfully operated tracking and interception a moving object. Furthermore, we proposed a MSDF control scheme, which combines the first one control scheme (PD+NN) and sensory data fusion model in the last part of this thesis. A visual/servo fusion model, an Elman neural network structure, was used to handle tracking process and to adapt itself through learning. We also verified the effectiveness of this scheme through visual/servo fusion control simulation of a SCORBOT ER VII robot manipulator to track a random moving target. This thesis consists of visual servoing, multisensor fusion and robot control for trajectory tracking. The main features of the MSDF control scheme are: (1) Data fusion is used for two disparate sensors. (2) Fusion mode is the mode-free and learning properties for the arbitrary motion tracking. (3) Robot motion control exhibits more robustness and adaptation.
Tsai, Bai-Li, and 蔡百里. "A Study on Travel Time Estimation Applications of Data Fusion Techniques." Thesis, 2004. http://ndltd.ncl.edu.tw/handle/41279504684983110548.
Full text淡江大學
運輸管理學系碩士班
94
In recent years, Government tries to carry out the development of Advanced Traveler Information System - among the nine service domains of Intelligent Information System. In order to provide accurate information for road users, to stand on the choices of routes and transportation, estimating the path travel time is an important issue. To estimate travel time, vehicle detectors and probe vehicles collecting information (e.g., flow, occupancy and speed, etc.) are being used. For the moment, there is quite few vehicle detectors can still be used. Under the insufficient resource and budget, it is uneasy to set up vehicle detectors widely, otherwise, to add probe vehicles in the short term to make up for the shortage of information gathering. This study applies the concept of vehicle speed distributes in space of roadway segment and intends to investigate how many probe vehicles are enough to describe or estimate travel time for a roadway segment. The aspect of investigation is a roadway segment or a roadway segment containing intersection, according to the concept of a sample distribution which reflects population characteristics. As a result, probe vehicle can be considered as an instantaneous fixed vehicle detector by using the instantaneous speed and position of probe vehicles and it sets up a speed distribution of samples, from the inside, explores the size of probe vehicles and reflects population to estimate instantaneous travel time. Furthermore, by using the instantaneous sample method and vehicle detector data to test the data fusion, the feasibility of this method will be determined. After conferring the size of probe vehicle, data collection through real network and establishment of the simulation network can be used when parameters are evaluated. To collect data from vehicle detectors and probe vehicles through simulation, and then carrying out data fusion to estimate travel time. Vehicle detector estimates density by using flow and occupancy rate, accords with OH and Webster model to estimate travel time, and matches up the travel time which probe vehicles drive end of the roadway segment. For this reason, this study contains: (1) Investigate and test the algorithm of probe vehicle size. (2) The comparison and suitable situation of data fusion. (3) Estimate travel time using data fusion, and hope to provide more accurate travel information for road user. The result of this study exhibits that sizes of the probe vehicle are more than other studies by using the instantaneous distribution of speed. According to different length and flow rate of roadway segment with different probe vehicle size, it distributes about ten to sixty percent, and the average is similar to Tetsuhiro (2005) who brought up that forty percent probe vehicles can collect traffic information nonstop. Besides, the test of data fusion uses instantaneous sampling method and the result exhibits that Weighted Average is better in the one roadway segment case, Artificial Neural Network is better in the two roadway segments case, and data fusion can reduce the travel time errors from each detector has estimated. The result of data fusion exhibits that Weighted Average is suitable for the road length under 400 meters, probe vehicle rate upon 10 percent, and update in 3 minutes (i.e., real time); Artificial Neural Network is suitable for the road length upon 400 meters, probe vehicle rate under 10 percent, and update in 5 minutes (i.e., comparatively longer time). Finally, advantages and disadvantages of two methods are provided for the related applications.
Shi, Bo-Yuan, and 施博元. "Mobile Vehicle Location Estimation using Wireless Communication Landmarks and Data Fusion Techniques." Thesis, 2006. http://ndltd.ncl.edu.tw/handle/46442003243322567468.
Full text育達商業技術學院
資訊管理所
94
[Abstract] The mobile location is to continuously confirm the position, direction, and velocity of a mobile vehicle. When the vehicle move, the vehicle’s position, velocity and direction have to be known and predicted. The mobile vehicle has to confirm its position and the trajectory for not being lost. Global Positioning System (GPS) is often utilized to eliminate the accumulated error from the Inertial Navigation System (INS). However, the accuracy of GPS positioning is highly related to the number and distribution of the available GPS satellites being tracked. This research uses the landmark of wireless communication by using the pseudo-satellite (pseudolite, PL), which is a ground-based GPS satellite-like signal transmitter. The problem dealt with here is that of estimating the kinematic state components of a vehicle in autonomous navigation using range, elevation and azimuth angles measured by Line of Sight (LOS) coordinate system. The estimates of the absolute position and velocity of the vehicle in Local Inertial Cartesian Coordinate System (LICCS) are provided by Kalman filter and the data fusion algorithm called covariance matching method. Performance results for the proposed algorithm are compared with those of Kalman filters, using difference simulations of typical vehicle maneuvering scenarios. Results of this research show that the Averaged Root Mean Square Error (ARMSE) of position and velocity with the filters was found to be larger (about 26% and 8%) than with the data fusion. Keyword:Landmark, Kalman Filter, Data Fusion.
林明輝. "The Application of Data Fusion Techniques in Cellular-based Radio Location System." Thesis, 2003. http://ndltd.ncl.edu.tw/handle/57296449779899686124.
Full text長庚大學
電機工程研究所
91
This thesis presents data fusion methods for wireless location systems. Time-base wireless location systems are usually based on the processing of time-of-arrival (TOA) or time-difference-of-arrival (TDOA). In TOA and TDOA systems, different geometric locations of mobile stations and base stations may result in GDOP errors. Data fusion techniques are usually used in multisensor system. The conception of data fusion is to increase the accuracy of system by combining measurements from multisensor. By utilizing data fusion methods to process the measures of TOA and TDOA effectively, we can reduce the effects of GDOP error and increase the accuracy of wireless location systems. Non-line-of-sight (NLOS) is the major error source in wireless location systems. The mitigation of NLOS errors by using line-of-sight (LOS) reconstruction technique is discussed. In this thesis, three data fusion techniques, including Bayes rules, Dempster-Shafer evidential reasoning, and fuzzy logic are presented. The data fusion methods and LOS reconstruction technique are applied in TOA and TDOA wireless location systems. Simulation results show that the structures with data fusion methods effective increase the accuracy of wireless location systems.
Chen, Jing-Cheng, and 陳滰埕. "Study of Experimental Design and Data Fusion Techniques to Construction Engineering Application." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/2f5a3t.
Full text國立臺灣科技大學
營建工程系
105
There are many uncertainties in construction engineering problem, such as structure safety detection, reliability analysis, building damage detection. Their experiment results vary because they could be influenced by many internal and external factors. In order to make the detection complete, it is necessary to use experimental design to explore all possible factors and then to apply data fusion to conclude the results. This study takes the pipeline leak detection as an example to test the above-mentioned process. This research designs possible water network condition using design of experiement (DOE). We set demand’s measurement data and supply pressure as input and use simulation software to simulate water network conditions. Then we get pipe flow initial parameters and put into optimization algorithm to calibrate them. After that, the concepts of volume balance and tolerance design are used to determine the leakage. Finally, using data fusion techniques analyze leak probability.