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Tesis sobre el tema "Linear discriminant analysis"

Autor: Grafiati

Publicado: 4 de junio de 2021

Última modificación: 25 de julio de 2025

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1

Skinner, Evelina. "Linear Discriminant Analysis with Repeated Measurements." Thesis, Linköpings universitet, Matematisk statistik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-162777.

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The classification of observations based on repeated measurements performed on the same subject over a given period of time or under different conditions is a common procedure in many disciplines such as medicine, psychology and environmental studies. In this thesis repeated measurements follow the Growth Curve model and are classified using linear discriminant analysis. The aim of this thesis is both to examine the effect of missing data on classification accuracy and to examine the effect of additional data on classification robustness. The results indicate that an increasing amount of missi

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2

Ganeshanandam, S. "Variable selection in two-group discriminant analysis using the linear discriminant function." Thesis, University of Reading, 1987. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.379265.

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3

Kim, Jiae. "Nonlinear Generalizations of Linear Discriminant Analysis: the Geometry of the Common Variance Space and Kernel Discriminant Analysis." The Ohio State University, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=osu1607019187556971.

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4

Li, Yongping. "Linear discriminant analysis and its application to face identification." Thesis, University of Surrey, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.326513.

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5

Calderini, Matias. "Linear Discriminant Analysis and Noise Correlations in Neuronal Activity." Thesis, Université d'Ottawa / University of Ottawa, 2019. http://hdl.handle.net/10393/39962.

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The effects of noise correlations on neuronal stimulus discrimination have been the subject of sustained debate. Both experimental and computational work suggest beneficial and detrimental contributions of noise correlations. The aim of this study is to develop an analytically tractable model of stimulus discrimination that reveals the conditions leading to improved or impaired performance from model parameters and levels of noise correlation. We begin with a mean firing rate integrator model as an approximation of underlying spiking activity in neuronal circuits. We consider two independent

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6

Nguyen, Hoang-Huy [Verfasser]. "Multi-Step Linear Discriminant Analysis and Its Applications / Hoang Huy Nguyen." Greifswald : Universitätsbibliothek Greifswald, 2013. http://d-nb.info/1030246793/34.

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7

Van, Deventer Petrus Jacobus Uys. "Outliers, influential observations and robust estimation in non-linear regression analysis and discriminant analysis." Doctoral thesis, University of Cape Town, 1993. http://hdl.handle.net/11427/4363.

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8

Draper, John Daniel. "Simultaneous Adaptive Fractional Discriminant Analysis: Applications to the Face Recognition Problem." The Ohio State University, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=osu1331096665.

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9

NAKAGAWA, Seiichi, Norihide KITAOKA, and Makoto SAKAI. "Linear Discriminant Analysis Using a Generalized Mean of Class Covariances and Its Application to Speech Recognition." Institute of Electronics, Information and Communication Engineers, 2008. http://hdl.handle.net/2237/14967.

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10

Hennon, Christopher C. "Investigating Probabilistic Forecasting of Tropical Cyclogenesis Over the North Atlantic Using Linear and Non-Linear Classifiers." The Ohio State University, 2003. http://rave.ohiolink.edu/etdc/view?acc_num=osu1047237423.

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11

Tekinay, Cagri. "Classification Of Remotely Sensed Data By Using 2d Local Discriminant Bases." Master's thesis, METU, 2009. http://etd.lib.metu.edu.tr/upload/3/12610782/index.pdf.

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In this thesis, 2D Local Discriminant Bases (LDB) algorithm is used to 2D search structure to classify remotely sensed data. 2D Linear Discriminant Analysis (LDA) method is converted into an M-ary classifier by combining majority voting principle and linear distance parameters. The feature extraction algorithm extracts the relevant features by removing the irrelevant ones and/or combining the ones which do not represent supplemental information on their own. The algorithm is implemented on a remotely sensed airborne data set from Tippecanoe County, Indiana to evaluate its performance. The spec

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12

Khosla, Nitin, and n/a. "Dimensionality Reduction Using Factor Analysis." Griffith University. School of Engineering, 2006. http://www4.gu.edu.au:8080/adt-root/public/adt-QGU20061010.151217.

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In many pattern recognition applications, a large number of features are extracted in order to ensure an accurate classification of unknown classes. One way to solve the problems of high dimensions is to first reduce the dimensionality of the data to a manageable size, keeping as much of the original information as possible and then feed the reduced-dimensional data into a pattern recognition system. In this situation, dimensionality reduction process becomes the pre-processing stage of the pattern recognition system. In addition to this, probablility density estimation, with fewer variables i

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13

Khosla, Nitin. "Dimensionality Reduction Using Factor Analysis." Thesis, Griffith University, 2006. http://hdl.handle.net/10072/366058.

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In many pattern recognition applications, a large number of features are extracted in order to ensure an accurate classification of unknown classes. One way to solve the problems of high dimensions is to first reduce the dimensionality of the data to a manageable size, keeping as much of the original information as possible and then feed the reduced-dimensional data into a pattern recognition system. In this situation, dimensionality reduction process becomes the pre-processing stage of the pattern recognition system. In addition to this, probablility density estimation, with fewer variables i

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14

Strong, Stephen. "Dimensionality Reduction for the Purposes of Automatic Pattern Classification." Thesis, Griffith University, 2013. http://hdl.handle.net/10072/367333.

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Pattern classification is a common technique used in a variety of applications. From simple tasks, such as password acceptance, to more complex tasks, such as identication by biometrics, speech recognition, and text recognition. As a result, a large number of pattern classification algorithms have emerged, allowing computers to perform these tasks. However, these techniques become less eective when excessive data on a given object is provided in comparison to the number of samples required to train. As a result, much research has been placed in nding ecient methods of reducing the dimensionali

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15

Azarmehr, Ramin. "Real-time Embedded Age and Gender Classification in Unconstrained Video." Thesis, Université d'Ottawa / University of Ottawa, 2015. http://hdl.handle.net/10393/32463.

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Recently, automatic demographic classification has found its way into embedded applications such as targeted advertising in mobile devices, and in-car warning systems for elderly drivers. In this thesis, we present a complete framework for video-based gender classification and age estimation which can perform accurately on embedded systems in real-time and under unconstrained conditions. We propose a segmental dimensionality reduction technique utilizing Enhanced Discriminant Analysis (EDA) to minimize the memory and computational requirements, and enable the implementation of these classifier

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16

Zaeri, Naser. "Computation and memory efficient face recognition using binarized eigenphases and component-based linear discriminant analysis for wide range applications." Thesis, University of Surrey, 2007. http://epubs.surrey.ac.uk/844078/.

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Face recognition finds many important applications in many life sectors and in particular in commercial and law enforcement. This thesis presents two novel methods which make face recognition more practical. In the first method, we propose an attractive solution for efficient face recognition systems that utilize low memory devices. The new technique applies the principal component analysis to the binarized phase spectrum of the Fourier transform of the covariance matrix constructed from the MPEG-7 Fourier Feature Descriptor vectors of the face images. Most of the algorithms proposed for face

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17

Padovani, Carlos Roberto [UNESP]. "Aplicativo computacional para obtenção de probabilidades a priori de classificação errônea em experimentos agronômicos." Universidade Estadual Paulista (UNESP), 2007. http://hdl.handle.net/11449/101872.

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Made available in DSpace on 2014-06-11T19:31:37Z (GMT). No. of bitstreams: 0 Previous issue date: 2007-07-27Bitstream added on 2014-06-13T21:02:58Z : No. of bitstreams: 1 padovani_crp_dr_botfca.pdf: 793418 bytes, checksum: 8b62c9d520c0086c46554fb418856bb7 (MD5)<br>Nas Ciências Agronômicas, encontram-se várias situações em que são observadas diversas variáveis respostas nas parcelas ou unidades experimentais. Nestas situações, um caso de interesse prático à experimentação agronômica é o que considera a construção de regiões de similaridade entre as parcelas para a discriminação entre os grupo

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18

Wilgenbus, Erich Feodor. "The file fragment classification problem : a combined neural network and linear programming discriminant model approach / Erich Feodor Wilgenbus." Thesis, North-West University, 2013. http://hdl.handle.net/10394/10215.

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The increased use of digital media to store legal, as well as illegal data, has created the need for specialized tools that can monitor, control and even recover this data. An important task in computer forensics and security is to identify the true le type to which a computer le or computer le fragment belongs. File type identi cation is traditionally done by means of metadata, such as le extensions and le header and footer signatures. As a result, traditional metadata-based le object type identi cation techniques work well in cases where the required metadata is available and unaltered

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19

Almeida, Larissa Medeiros de. "Avaliação da gravidade da malária utilizando técnicas de extração de características e redes neurais artificiais." Universidade Federal do Amazonas, 2015. http://tede.ufam.edu.br/handle/tede/4093.

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Submitted by Kamila Costa (kamilavasconceloscosta@gmail.com) on 2015-06-15T21:53:52Z No. of bitstreams: 1 Dissertação-Larissa M de Almeida.pdf: 5516102 bytes, checksum: e49d2bccd21168f811140c6accd54e8f (MD5)<br>Approved for entry into archive by Divisão de Documentação/BC Biblioteca Central (ddbc@ufam.edu.br) on 2015-06-16T15:05:39Z (GMT) No. of bitstreams: 1 Dissertação-Larissa M de Almeida.pdf: 5516102 bytes, checksum: e49d2bccd21168f811140c6accd54e8f (MD5)<br>Approved for entry into archive by Divisão de Documentação/BC Biblioteca Central (ddbc@ufam.edu.br) on 2015-06-16T15:07:25Z (GMT)

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20

Umunoza, Gasana Emelyne. "Misclassification Probabilities through Edgeworth-type Expansion for the Distribution of the Maximum Likelihood based Discriminant Function." Licentiate thesis, Linköpings universitet, Tillämpad matematik, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-175873.

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This thesis covers misclassification probabilities via an Edgeworth-type expansion of the maximum likelihood based discriminant function. When deriving misclassification errors, first the expectation and variance in the population are assumed to be known where the variance is the same across populations and thereafter we consider the case where those parameters are unknown. Cumulants of the discriminant function for discriminating between two multivariate normal populations are derived. Approximate probabilities of the misclassification errors are established via an Edgeworth-type expansion us

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21

Shin, Hyejin. "Infinite dimensional discrimination and classification." Texas A&M University, 2003. http://hdl.handle.net/1969.1/5832.

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Modern data collection methods are now frequently returning observations that should be viewed as the result of digitized recording or sampling from stochastic processes rather than vectors of finite length. In spite of great demands, only a few classification methodologies for such data have been suggested and supporting theory is quite limited. The focus of this dissertation is on discrimination and classification in this infinite dimensional setting. The methodology and theory we develop are based on the abstract canonical correlation concept of Eubank and Hsing (2005), and motivated by the

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22

Padovani, Carlos Roberto Pereira 1975. "Aplicativo computacional para obtenção de probabilidades a priori de classificação errônea em experimentos agronômicos /." Botucatu : [s.n.], 2007. http://hdl.handle.net/11449/101872.

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Orientador: Flávio Ferrari Aragon<br>Banca: Adriano Wagner Ballarin<br>Banca: Luís Fernando Nicolosi Bravin<br>Banca: Rui Vieira de Moraes<br>Banca: Sandra Fiorelli de Almeida P. Simeão<br>Resumo: Nas Ciências Agronômicas, encontram-se várias situações em que são observadas diversas variáveis respostas nas parcelas ou unidades experimentais. Nestas situações, um caso de interesse prático à experimentação agronômica é o que considera a construção de regiões de similaridade entre as parcelas para a discriminação entre os grupos experimentais e ou para a classificação de novas unidades experiment

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23

Arpaci, Erdogan. "Analysis Of Sinusoidal And Helical Buckling Of Drill String In Horizontal Wells Using Finite Element Method." Master's thesis, METU, 2009. http://etd.lib.metu.edu.tr/upload/2/12611003/index.pdf.

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The number of horizontal wells is increasing rapidly in all over the world with the growth of new technological developments. During horizontal well drilling, much more complex problems occur when compared with vertical well drilling, such as decrease in load transfer to the bit, tubular failure, tubular fatigue and tubular lock-up. This makes selection of appropriate tubular and making the right drill string design more important. As the total compression load on the horizontal section increases, the behavior of the tubular changes from straight to sinusoidal buckling, and if the total compre

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24

Mauk, Rachel Grant. "Prediction of Intensity Change Subsequent to Concentric Eyewall Events." The Ohio State University, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=osu1469037273.

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25

Milanez, Karla Danielle Tavares de Melo. "Classificação de óleos vegetais comestíveis usando imagens digitais e técnicas de reconhecimento de padrões." Universidade Federal da Paraíba, 2013. http://tede.biblioteca.ufpb.br:8080/handle/tede/7157.

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Made available in DSpace on 2015-05-14T13:21:42Z (GMT). No. of bitstreams: 1 arquivototal.pdf: 3270377 bytes, checksum: f7faeeb5a1fdf2284d994edc54a6a265 (MD5) Previous issue date: 2013-08-26<br>Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES<br>This work presents a simple and non-expensive based on digital image and pattern recognition techniques for the classification of edible vegetable oils with respect to the type (soybean, canola, sunflower and corn) and the conservation state (expired and non-expired period of validity). For this, images of the sample oils were ob

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26

DUARTE, Daniel Duarte. "Classificação de lesões em mamografias por análise de componentes independentes, análise discriminante linear e máquina de vetor de suporte." Universidade Federal do Maranhão, 2008. http://tedebc.ufma.br:8080/jspui/handle/tede/1816.

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Submitted by Rosivalda Pereira (mrs.pereira@ufma.br) on 2017-08-14T18:15:08Z No. of bitstreams: 1 DanielCosta.pdf: 1087754 bytes, checksum: ada5f863f42efd8298fff788c37bded3 (MD5)<br>Made available in DSpace on 2017-08-14T18:15:08Z (GMT). No. of bitstreams: 1 DanielCosta.pdf: 1087754 bytes, checksum: ada5f863f42efd8298fff788c37bded3 (MD5) Previous issue date: 2008-02-25<br>Female breast cancer is the major cause of death in western countries. Efforts in Computer Vision have been made in order to add improve the diagnostic accuracy by radiologists. In this work, we present a methodology th

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27

Åman, Agnes. "Predicting consultation durations in a digital primary care setting." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-231921.

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The aim of this thesis is to develop a method to predict consultation durations in a digital primary care setting and thereby create a tool for designing a more efficient scheduling system in primary care. The ultimate purpose of the work is to contribute to a reduction in waiting times in primary care. Even though no actual scheduling system was implemented, four machine learning models were implemented and compared to see if any of them had better performance. The input data used in this study was a combination of patient and doctor features. The patient features consisted of information ext

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28

Elnady, Maged Elsaid. "On-shaft vibration measurement using a MEMS accelerometer for faults diagnosis in rotating machines." Thesis, University of Manchester, 2013. https://www.research.manchester.ac.uk/portal/en/theses/onshaft-vibration-measurement-using-a-mems-accelerometer-for-faults-diagnosis-in-rotating-machines(cf9b9848-972d-49ff-a6b0-97bef1ad0e93).html.

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The healthy condition of a rotating machine leads to safe and cheap operation of almost all industrial facilities and mechanical systems. To achieve such a goal, vibration-based condition monitoring has proved to be a well-accepted technique that detects incipient fault symptoms. The conventional way of On-Bearing Vibration Measurement (OBVM) captures symptoms of different faults, however, it requires a relatively expensive setup, an additional space for the auxiliary devices and cabling in addition to an experienced analyst. On-Shaft Vibration Measurement (OSVM) is an emerging method proposed

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29

Švábek, Hynek. "Nalezení a rozpoznání dominantních rysů obličeje." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2010. http://www.nusl.cz/ntk/nusl-237180.

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This thesis deals with the increasingly developing field of biometric systems which is the identification of faces. The thesis deals with the possibilities of face localization in pictures and their normalization, which is necessary due to external influences and the influence of different scanning techniques. It describes various techniques of localization of dominant features of the face such as eyes, mouth or nose. Not least, it describes different approaches to the identification of faces. Furthermore a it deals with an implementation of the Dominant Face Features Recognition application,

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30

Salmon, Elizabeth. "DEVELOPMENT OF AN EEG BRAIN-MACHINE INTERFACE TO AID IN RECOVERY OF MOTOR FUNCTION AFTER NEUROLOGICAL INJURY." UKnowledge, 2013. http://uknowledge.uky.edu/cbme_etds/8.

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Impaired motor function following neurological injury may be overcome through therapies that induce neuroplastic changes in the brain. Therapeutic methods include repetitive exercises that promote use-dependent plasticity (UDP), the benefit of which may be increased by first administering peripheral nerve stimulation (PNS) to activate afferent fibers, resulting in increased cortical excitability. We speculate that PNS delivered only in response to attempted movement would induce timing-dependent plasticity (TDP), a mechanism essential to normal motor learning. Here we develop a brain-machine i

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31

Gul, Ahmet Bahtiyar. "Holistic Face Recognition By Dimension Reduction." Master's thesis, METU, 2003. http://etd.lib.metu.edu.tr/upload/1056738/index.pdf.

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Face recognition is a popular research area where there are different approaches studied in the literature. In this thesis, a holistic Principal Component Analysis (PCA) based method, namely Eigenface method is studied in detail and three of the methods based on the Eigenface method are compared. These are the Bayesian PCA where Bayesian classifier is applied after dimension reduction with PCA, the Subspace Linear Discriminant Analysis (LDA) where LDA is applied after PCA and Eigenface where Nearest Mean Classifier applied after PCA. All the three methods are implemented on the Olivetti Resear

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32

Gao, Hui. "Extracting key features for analysis and recognition in computer vision." Columbus, Ohio : Ohio State University, 2006. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1141770523.

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33

Gooch, Steven R. "A METHOD FOR NON-INVASIVE, AUTOMATED BEHAVIOR CLASSIFICATION IN MICE, USING PIEZOELECTRIC PRESSURE SENSORS." UKnowledge, 2014. http://uknowledge.uky.edu/ece_etds/56.

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While all mammals sleep, the functions and implications of sleep are not well understood, and are a strong area of investigation in the research community. Mice are utilized in many sleep studies, with electroencephalography (EEG) signals widely used for data acquisition and analysis. However, since EEG electrodes must be surgically implanted in the mice, the method is high cost and time intensive. This work presents an extension of a previously researched high throughput, low cost, non-invasive method for mouse behavior detection and classification. A novel hierarchical classifier is presente

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34

Kim, Seongsu. "A BAYESIAN EVIDENCE DEFINING SEARCH." The Ohio State University, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=osu1429789001.

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35

Vaizurs, Raja Sarath Chandra Prasad. "Atrial Fibrillation Signal Analysis." Scholar Commons, 2011. http://scholarcommons.usf.edu/etd/3386.

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Atrial fibrillation (AF) is the most common type of cardiac arrhythmia encountered in clinical practice and is associated with an increased mortality and morbidity. Identification of the sources of AF has been a goal of researchers for over 20 years. Current treatment procedures such as Cardio version, Radio Frequency Ablation, and multiple drugs have reduced the incidence of AF. Nevertheless, the success rate of these treatments is only 35-40% of the AF patients as they have limited effect in maintaining the patient in normal sinus rhythm. The problem stems from the fact that there are no me

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36

Ribeiro, Lucas de Almeida. "Algoritmo evolutivo multi-objetivo em tabelas para seleção de variáveis em classificação multivariada." Universidade Federal de Goiás, 2014. http://repositorio.bc.ufg.br/tede/handle/tede/4405.

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37

Zhang, Angang. "Some Advances in Classifying and Modeling Complex Data." Diss., Virginia Tech, 2015. http://hdl.handle.net/10919/77958.

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In statistical methodology of analyzing data, two of the most commonly used techniques are classification and regression modeling. As scientific technology progresses rapidly, complex data often occurs and requires novel classification and regression modeling methodologies according to the data structure. In this dissertation, I mainly focus on developing a few approaches for analyzing the data with complex structures. Classification problems commonly occur in many areas such as biomedical, marketing, sociology and image recognition. Among various classification methods, linear classifiers ha

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38

Bayik, Tuba Makbule. "Automatic Target Recognition In Infrared Imagery." Master's thesis, METU, 2004. http://etd.lib.metu.edu.tr/upload/2/12605388/index.pdf.

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The task of automatically recognizing targets in IR imagery has a history of approximately 25 years of research and development. ATR is an application of pattern recognition and scene analysis in the field of defense industry and it is still one of the challenging problems. This thesis may be viewed as an exploratory study of ATR problem with encouraging recognition algorithms implemented in the area. The examined algorithms are among the solutions to the ATR problem, which are reported to have good performance in the literature. Throughout the study, PCA, subspace LDA, ICA, nearest mean class

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39

Pacola, Edras Reily. "Uso da análise de discriminante linear em conjunto com a transformada wavelet discreta no reconhecimento de espículas." Universidade Tecnológica Federal do Paraná, 2015. http://repositorio.utfpr.edu.br/jspui/handle/1/1828.

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CAPES<br>Pesquisadores têm concentrado esforços, nos últimos 20 anos, aplicando a transformada wavelet no processamento, filtragem, reconhecimento de padrões e na classificação de sinais biomédicos, especificamente em sinais de eletroencefalografia (EEG) contendo eventos característicos da epilepsia, as espículas. Várias famílias de wavelets-mães foram utilizadas, mas sem um consenso sobre qual wavelet-mãe é a mais adequada para essa finalidade. Os sinais utilizados apresentam uma gama muito grande de eventos e não possuem características padronizadas. A literatura relata sinais de EEG amostra

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40

Kartheek, arun sai ram chilla, and Chelluboina Kavya. "Investigating Metrics that are Good Predictors of Human Oracle Costs An Experiment." Thesis, Blekinge Tekniska Högskola, Institutionen för programvaruteknik, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-14080.

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Context. Human oracle cost, the cost associated in estimating the correctness of the output for the given test inputs is manually evaluated by humans and this cost is significant and is a concern in the software test data generation field. This study has been designed in the context to assess metrics that might predict human oracle cost. Objectives. The major objective of this study is to address the human oracle cost, for this the study identifies the metrics that are good predictors of human oracle cost and can further help to solve the oracle problem. In this process, the identified suitabl

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41

Feng, Qianli. "Automatic American Sign Language Imitation Evaluator." The Ohio State University, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=osu1461233570.

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42

Einestam, Ragnar, and Karl Casserfelt. "PiEye in the Wild: Exploring Eye Contact Detection for Small Inexpensive Hardware." Thesis, Malmö högskola, Fakulteten för teknik och samhälle (TS), 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:mau:diva-20696.

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Ögonkontakt-sensorer skapar möjligheten att tolka användarens uppmärksamhet, vilketkan användas av system på en mängd olika vis. Dessa inkluderar att skapa nya möjligheterför människa-dator-interaktion och mäta mönster i uppmärksamhet hos individer.I den här uppsatsen gör vi ett försök till att konstruera en ögonkontakt-sensor med hjälpav en Raspberry Pi, med målet att göra den praktisk i verkliga scenarion. För att fastställaatt den är praktisk satte vi upp ett antal kriterier baserat på tidigare användning avögonkontakt-sensorer. För att möta dessa kriterier valde vi att använda en maskininl

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Onder, Murat. "Face Detection And Active Robot Vision." Master's thesis, METU, 2004. http://etd.lib.metu.edu.tr/upload/2/12605290/index.pdf.

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The main task in this thesis is to design a robot vision system with face detection and tracking capability. Hence there are two main works in the thesis: Firstly, the detection of the face on an image that is taken from the camera on the robot must be achieved. Hence this is a serious real time image processing task and time constraints are very important because of this reason. A processing rate of 1 frame/second is tried to be achieved and hence a fast face detection algorithm had to be used. The Eigenface method and the Subspace LDA (Linear Discriminant Analysis) method are implemented, te

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Wang, Xuechuan, and n/a. "Feature Extraction and Dimensionality Reduction in Pattern Recognition and Their Application in Speech Recognition." Griffith University. School of Microelectronic Engineering, 2003. http://www4.gu.edu.au:8080/adt-root/public/adt-QGU20030619.162803.

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Conventional pattern recognition systems have two components: feature analysis and pattern classification. Feature analysis is achieved in two steps: parameter extraction step and feature extraction step. In the parameter extraction step, information relevant for pattern classification is extracted from the input data in the form of parameter vector. In the feature extraction step, the parameter vector is transformed to a feature vector. Feature extraction can be conducted independently or jointly with either parameter extraction or classification. Linear Discriminant Analysis (LDA) and Princi

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Wang, Xuechuan. "Feature Extraction and Dimensionality Reduction in Pattern Recognition and Their Application in Speech Recognition." Thesis, Griffith University, 2003. http://hdl.handle.net/10072/365680.

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Conventional pattern recognition systems have two components: feature analysis and pattern classification. Feature analysis is achieved in two steps: parameter extraction step and feature extraction step. In the parameter extraction step, information relevant for pattern classification is extracted from the input data in the form of parameter vector. In the feature extraction step, the parameter vector is transformed to a feature vector. Feature extraction can be conducted independently or jointly with either parameter extraction or classification. Linear Discriminant Analysis (LDA) and Princi

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46

Sanchez, Merchante Luis Francisco. "Learning algorithms for sparse classification." Phd thesis, Université de Technologie de Compiègne, 2013. http://tel.archives-ouvertes.fr/tel-00868847.

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This thesis deals with the development of estimation algorithms with embedded feature selection the context of high dimensional data, in the supervised and unsupervised frameworks. The contributions of this work are materialized by two algorithms, GLOSS for the supervised domain and Mix-GLOSS for unsupervised counterpart. Both algorithms are based on the resolution of optimal scoring regression regularized with a quadratic formulation of the group-Lasso penalty which encourages the removal of uninformative features. The theoretical foundations that prove that a group-Lasso penalized optimal sc

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47

Janbain, Ali. "Utilisation d'algorithmes génétiques pour l'identification systématique de réseaux de gènes co-régulés." Thesis, Montpellier, 2019. http://www.theses.fr/2019MONTT019/document.

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L’objectif de ce travail est de mettre au point une nouvelle approche automatique pour identifier les réseaux de gènes concourant à une même fonction biologique. Ceci permet une meilleure compréhension des phénomènes biologiques et notamment des processus impliqués dans les maladies telles que les cancers. Différentes stratégies ont été développées pour essayer de regrouper les gènes d’un organisme selon leurs relations fonctionnelles : génétique classique et génétique moléculaire. Ici, nous utilisons une propriété connue des réseaux de gènes fonctionnellement liés à savoir que ces gènes sont

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Macenauer, Oto. "Identifikace obličeje." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2010. http://www.nusl.cz/ntk/nusl-237221.

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This document introduces the reader to area of face recognition. Miscellaneous methods are mentioned and categorized to be able to understand the process of face recognition. Main focus of this document is on issues of current face recognition and possibilities do solve these inconveniences in order to be able to massively spread face recognition. The second part of this work is focused on implementation of selected methods, which are Linear Discriminant Analysis and Principal Component Analysis. Those methods are compared to each other and results are given at the end of work.

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Zhong, Xiao. "A study of several statistical methods for classification with application to microbial source tracking." Link to electronic thesis, 2004. http://www.wpi.edu/Pubs/ETD/Available/etd-0430104-155106/.

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Thesis (M.S.)--Worcester Polytechnic Institute.<br>Keywords: classification; k-nearest-neighbor (k-n-n); neural networks; linear discriminant analysis (LDA); support vector machines; microbial source tracking (MST); quadratic discriminant analysis (QDA); logistic regression. Includes bibliographical references (p. 59-61).

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Novotný, Ondřej. "Adaptace systémů pro rozpoznání mluvčího." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2014. http://www.nusl.cz/ntk/nusl-236084.

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In this paper, we propose techniques for adaptation of speaker recognition systems. The aim of this work is to create adaptation for Probabilistic Linear Discriminant Analysis. Special attention is given to unsupervised adaptation. Our test shows appropriate clustering techniques for speaker estimation of the identity and estimation of the number of speakers in adaptation dataset. For the test, we are using NIST and Switchboard corpora.

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