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Dissertations / Theses on the topic 'Gesture classification and feature extraction'

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Published: 4 June 2025

Last updated: 1 August 2025

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1

Goodman, Steve. "Feature extraction and classification." Thesis, University of Sunderland, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.301872.

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2

Liu, Raymond. "Feature extraction in classification." Thesis, Imperial College London, 2013. http://hdl.handle.net/10044/1/23634.

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Feature extraction, or dimensionality reduction, is an essential part of many machine learning applications. The necessity for feature extraction stems from the curse of dimensionality and the high computational cost of manipulating high-dimensional data. In this thesis we focus on feature extraction for classification. There are several approaches, and we will focus on two such: the increasingly popular information-theoretic approach, and the classical distance-based, or variance-based approach. Current algorithms for information-theoretic feature extraction are usually iterative. In contrast

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3

Elliott, Rodney Bruce. "Feature extraction techniques for grasp classification." Thesis, University of Canterbury. Mechanical Engineering, 1998. http://hdl.handle.net/10092/3447.

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This thesis examines the ability of four signal parameterisation techniques to provide discriminatory information between six different classes of signal. This was done with a view to assessing the suitability of the four techniques for inclusion in the real-time control scheme of a next generation robotic prosthesis. Each class of signal correlates to a particular type of grasp that the robotic prosthesis is able to form. Discrimination between the six classes of signal was done on the basis of parameters extracted from four channels of electromyographie (EMG) data that was recorded from musc

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4

Forsberg, Axel. "A Wavelet-Based Surface Electromyogram Feature Extraction for Hand Gesture Recognition." Thesis, Mälardalens högskola, Akademin för innovation, design och teknik, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-39766.

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The research field of robotic prosthetic hands have expanded immensely in the last couple of decades and prostheses are in more commercial use than ever. Classification of hand gestures using sensory data from electromyographic signals in the forearm are primary for any advanced prosthetic hand. Improving classification accuracy could lead to more user friendly and more naturally controlled prostheses. In this thesis, features were extracted from wavelet transform coefficients of four channel electromyographic data and used for classifying ten different hand gestures. Extensive search for suit

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5

Chaofan, Hao, and Yu Haisheng. "Feature Extraction of Gesture Recognition Based on Image Analysis by Using Matlab." Thesis, Högskolan i Gävle, Avdelningen för Industriell utveckling, IT och Samhällsbyggnad, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:hig:diva-17367.

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This thesis mainly focuses on the research of gesture extraction and finger segmentation in the gesture recognition. In this paper, we used image analysis technologies to create an application by encoding in Matlab program. We used this application to segment and extract the finger from one specific gesture (the gesture "one") and ran successfully. We explored the success rate of extracting the characteristic of the specific gesture "one" in different natural environments. We divided the natural environment into three different conditions which are glare and dark condition, similar object cond

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6

Chilo, José. "Feature extraction for low-frequency signal classification /." Stockholm : Fysik, Physics, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-4661.

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7

Aktaruzzaman, M. "FEATURE EXTRACTION AND CLASSIFICATION THROUGH ENTROPY MEASURES." Doctoral thesis, Università degli Studi di Milano, 2015. http://hdl.handle.net/2434/277947.

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Entropy is a universal concept that represents the uncertainty of a series of random events. The notion “entropy" is differently understood in different disciplines. In physics, it represents the thermodynamical state variable; in statistics it measures the degree of disorder. On the other hand, in computer science, it is used as a powerful tool for measuring the regularity (or complexity) in signals or time series. In this work, we have studied entropy based features in the context of signal processing. The purpose of feature extraction is to select the relevant features from an entity.

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8

Graf, Arnulf B. A. "Classification and feature extraction in man and machine." [S.l. : s.n.], 2004. http://deposit.ddb.de/cgi-bin/dokserv?idn=972533508.

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9

Hamsici, Onur C. "Bayes Optimality in Classification, Feature Extraction and Shape Analysis." The Ohio State University, 2008. http://rave.ohiolink.edu/etdc/view?acc_num=osu1218513562.

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10

Khan, Muhammad. "Hand Gesture Detection & Recognition System." Thesis, Högskolan Dalarna, Datateknik, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:du-6496.

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The project introduces an application using computer vision for Hand gesture recognition. A camera records a live video stream, from which a snapshot is taken with the help of interface. The system is trained for each type of count hand gestures (one, two, three, four, and five) at least once. After that a test gesture is given to it and the system tries to recognize it.A research was carried out on a number of algorithms that could best differentiate a hand gesture. It was found that the diagonal sum algorithm gave the highest accuracy rate. In the preprocessing phase, a self-developed algori

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11

Nilsson, Mikael. "On feature extraction and classification in speech and image processing /." Karlskrona : Department of Signal Processing, School of Engineering, Blekinge Institute of Technology, 2007. http://www.bth.se/fou/forskinfo.nsf/allfirst2/fcbe16e84a9ba028c12573920048bce9?OpenDocument.

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12

Coath, Martin. "A computational model of auditory feature extraction and sound classification." Thesis, University of Plymouth, 2005. http://hdl.handle.net/10026.1/1822.

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This thesis introduces a computer model that incorporates responses similar to those found in the cochlea, in sub-corticai auditory processing, and in auditory cortex. The principle aim of this work is to show that this can form the basis for a biologically plausible mechanism of auditory stimulus classification. We will show that this classification is robust to stimulus variation and time compression. In addition, the response of the system is shown to support multiple, concurrent, behaviourally relevant classifications of natural stimuli (speech). The model incorporates transient enhancemen

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13

Benn, David E. "Model-based feature extraction and classification for automatic face recognition." Thesis, University of Southampton, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.324811.

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14

Zheng, Yue Chu. "Feature extraction for chart pattern classification in financial time series." Thesis, University of Macau, 2018. http://umaclib3.umac.mo/record=b3950623.

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15

Meccio, Tony. "Feature Extraction and Randomized Learning for Image Analysis and Classification." Thesis, Università degli Studi di Catania, 2011. http://hdl.handle.net/10761/189.

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Research in Computer Vision has grown in interest over the years, up to the point where it became of interest for corporate research. The focus of this thesis is on studies which have been undertaken about designing Computer Vision applications for image analysis and classification in embedded systems. This research was funded by STMicroelectronics, AST Imaging, Catania Lab, and it is part of the activities of the Joint Lab between STMicroelectronics and the Image Processing Lab of the University of Catania.

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16

Jia, Jia. "Interactive Imaging via Hand Gesture Recognition." Thesis, University of Bradford, 2009. http://hdl.handle.net/10454/4259.

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With the growth of computer power, Digital Image Processing plays a more and more important role in the modern world, including the field of industry, medical, communications, spaceflight technology etc. As a sub-field, Interactive Image Processing emphasizes particularly on the communications between machine and human. The basic flowchart is definition of object, analysis and training phase, recognition and feedback. Generally speaking, the core issue is how we define the interesting object and track them more accurately in order to complete the interaction process successfully. This thesis

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Bekiroglu, Yasemi. "Nonstationary feature extraction techniques for automatic classification of impact acoustic signals." Thesis, Högskolan Dalarna, Datateknik, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:du-3592.

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Condition monitoring of wooden railway sleepers applications are generallycarried out by visual inspection and if necessary some impact acoustic examination iscarried out intuitively by skilled personnel. In this work, a pattern recognition solutionhas been proposed to automate the process for the achievement of robust results. Thestudy presents a comparison of several pattern recognition techniques together withvarious nonstationary feature extraction techniques for classification of impactacoustic emissions. Pattern classifiers such as multilayer perceptron, learning cectorquantization and g

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KHOSA, IKRAMULLAH. "Feature Extraction, Pattern Recognition and Classification in X-ray Image Data." Doctoral thesis, Politecnico di Torino, 2015. http://hdl.handle.net/11583/2588454.

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Excellence of food products highly depends on the quality checks at different stages while preparation and processing at industry. With the evolution of technology, traditional methods are being put back and state of the art equipment taking the position. Being fast, efficient and automatic, computers and machines are potentially replacing the human deployment in the food industry. One of the early stages of food preparation is the ingredient evaluation on feeding belt. This is still carried out mostly by humans; however efforts have been made for the development of such system which is capabl

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Paraskevas, Ioannis. "Phase as a feature extraction tool for audio classification and signal localisation." Thesis, University of Surrey, 2005. http://epubs.surrey.ac.uk/843856/.

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The aim of this research is to demonstrate the significance of signal phase content in time localization issues in synthetic signals and in the extraction of appropriate features from acoustically similar audio recordings (non-synthetic signals) for audio classification purposes. Published work, relating to audio classification, tends to be1 focused on the discrimination of audio classes that are dissimilar acoustically. Consequently, a wide range of features, extracted from the audio recordings, has been appropriate for the classification task. In this research, the audio classification appli

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20

Sernheim, Mikael. "Experimental Study on ClassifierDesign and Text Feature Extraction for Short Text Classification." Thesis, Uppsala universitet, Institutionen för informationsteknologi, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-323214.

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Text classification is a wide research field with existing ready-to-use solutions for supervised training of text classifiers. The task of classifying short texts puts dif-ferent demands on the invoked learning system that general text classification does not. This thesis explores this challenge by experimenting on how to design the clas-sification system and what text features granted the best results. In the experimental study, a hierarchical versus a flat design was compared, along with different aspects of text features. The method consisted of training and testing on a dataset of 3.2 mill

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21

Fargeas, Aureline. "Classification, feature extraction and prediction of side effects in prostate cancer radiotherapy." Thesis, Rennes 1, 2016. http://www.theses.fr/2016REN1S022/document.

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Le cancer de la prostate est l'un des cancers les plus fréquents chez l'homme. L'un des traitements standard est la radiothérapie externe, qui consiste à délivrer un rayonnement d'ionisation à une cible clinique, en l'occurrence la prostate et les vésicules séminales. Les objectifs de la radiothérapie externe sont la délivrance d'une dose d'irradiation maximale à la tumeur tout en épargnant les organes voisins (principalement le rectum et la vessie) pour éviter des complications suite au traitement. Comprendre les relations dose/toxicité est une question centrale pour améliorer la fiabilité du

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22

Dilger, Samantha Kirsten Nowik. "Pushing the boundaries: feature extraction from the lung improves pulmonary nodule classification." Diss., University of Iowa, 2016. https://ir.uiowa.edu/etd/3071.

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Lung cancer is the leading cause of cancer death in the United States. While low-dose computed tomography (CT) screening reduces lung cancer mortality by 20%, 97% of suspicious lesions are found to be benign upon further investigation. Computer-aided diagnosis (CAD) tools can improve the accuracy of CT screening, however, current CAD tools which focus on imaging characteristics of the nodule alone are challenged by the limited data captured in small, early identified nodules. We hypothesize a CAD tool that incorporates quantitative CT features from the surrounding lung parenchyma will improve

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23

Bradley, Andrew Peter. "Machine learning for medical diagnostics: Techniques for feature extraction, classification, and evaluation." Thesis, University of Queensland, 1996.

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The use of computers as diagnostic aids in medicine is becoming a reality in the clinical arena; a major factor to this trend being the successful application of machine learning techniques. Three fundamentally different approaches to machine learning have been identified, which we call Exemplar, Hyper-plane, and Hyper-rectangle based methods. Part of this thesis is devoted to a novel hyper- rectangle based algorithm called the Multiscale Classifier (MSC), which is implemented as an inductive decision tree. The MSC can be applied to any N-dimensional classification problem, successively splitt

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24

Magnusson, Ludvig, and Johan Rovala. "AI Approaches for Classification and Attribute Extraction in Text." Thesis, Linnéuniversitetet, Institutionen för datavetenskap (DV), 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-67882.

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As the amount of data online grows, the urge to use this data for different applications grows as well. Machine learning can be used with the intent to reconstruct and validate the data you are interested in. Although the problem is very domain specific, this report will attempt to shed some light on what we call strategies for classification, which in broad terms mean, a set of steps in a process where the end goal is to have classified some part of the original data. As a result, we hope to introduce clarity into the classification process in detail as well as from a broader perspective. The

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25

Masip, Rodó David. "Face Classification Using Discriminative Features and Classifier Combination." Doctoral thesis, Universitat Autònoma de Barcelona, 2005. http://hdl.handle.net/10803/3051.

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A mesura que la tecnologia evoluciona, apareixen noves aplicacions en el mon de la classificació facial. En el reconeixement de patrons, normalment veiem les cares com a punts en un espai de alta dimensionalitat definit pels valors dels seus pixels. Aquesta aproximació pateix diversos problemes: el fenomen de la "la maledicció de la dimensionalitat", la presència d'oclusions parcials o canvis locals en la il·luminació. Tradicionalment, només les característiques internes de les imatges facials s'han utilitzat per a classificar, on normalment es fa una extracció de característiques. Les tècniq

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26

Brown, Dane. "Investigating combinations of feature extraction and classification for improved image-based multimodal biometric systems at the feature level." Thesis, Rhodes University, 2018. http://hdl.handle.net/10962/63470.

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Multimodal biometrics has become a popular means of overcoming the limitations of unimodal biometric systems. However, the rich information particular to the feature level is of a complex nature and leveraging its potential without overfitting a classifier is not well studied. This research investigates feature-classifier combinations on the fingerprint, face, palmprint, and iris modalities to effectively fuse their feature vectors for a complementary result. The effects of different feature-classifier combinations are thus isolated to identify novel or improved algorithms. A new face segmenta

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27

Shang, Changjing. "Principal features based texture classification using artificial neural networks." Thesis, Heriot-Watt University, 1995. http://hdl.handle.net/10399/1323.

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28

Furuhashi, Takeshi, Tomohiro Yoshikawa, Kanta Tachibana, and Minh Tuan Pham. "Feature Extraction Based on Space Folding Model and Application to Machine Learning." 日本知能情報ファジィ学会, 2010. http://hdl.handle.net/2237/20689.

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Session ID: TH-F3-4<br>SCIS & ISIS 2010, Joint 5th International Conference on Soft Computing and Intelligent Systems and 11th International Symposium on Advanced Intelligent Systems. December 8-12, 2010, Okayama Convention Center, Okayama, Japan

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29

Ren, Bobby (Bobby B. ). "Calibration, feature extraction and classification of water contaminants using a differential mobility spectrometer." Thesis, Massachusetts Institute of Technology, 2006. http://hdl.handle.net/1721.1/53163.

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Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2006.<br>Includes bibliographical references (p. 87-89).<br>High-Field Asymmetric Waveform Ion Mobility Spectrometry (FAIMS) is a chemical sensor that separates ions in the gaseous phase based on their mobility in high electric fields. A threefold approach was developed for both chemical type classification and concentration classification of water contaminants for FAIMS signals. The three steps in this approach are calibration, feature extraction, and classification. Calibration was

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Zilberman, Eric R. "Autonomous time-frequency cropping and feature-extraction algorithms for classification of LPI radar modulations." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2006. http://library.nps.navy.mil/uhtbin/hyperion/06Jun%5FZilberman.pdf.

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31

Smith, R. S. "Angular feature extraction and ensemble classification method for 2D, 2.5D and 3D face recognition." Thesis, University of Surrey, 2008. http://epubs.surrey.ac.uk/843069/.

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It has been recognised that, within the context of face recognition, angular separation between centred feature vectors is a useful measure of dissimilarity. In this thesis we explore this observation in more detail and compare and contrast angular separation with the Euclidean, Manhattan and Mahalonobis distance metrics. This is applied to 2D, 2.5D and 3D face images and the investigation is done in conjunction with various feature extraction techniques such as local binary patterns (LBP) and linear discriminant analysis (LDA). We also employ error-correcting output code (ECOC) ensembles of s

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Schnur, Steven R. "Identification and classification of OFDM based signals using preamble correlation and cyclostationary feature extraction." Thesis, Monterey, California : Naval Postgraduate School, 2009. http://edocs.nps.edu/npspubs/scholarly/theses/2009/Sep/09Sep%5FSchnur.pdf.

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Thesis (M.S. in Electrical Engineering)--Naval Postgraduate School, September 2009.<br>Thesis Advisor(s): Tummala, Murali ; McEachen, John. "September 2009." Description based on title screen as viewed on November 5, 2009. Author(s) subject terms: IEEE 802.11, IEEE 802.16, OFDM, Cyclostationary Feature Extraction, FFT Accumulation Method. Includes bibliographical references (p. 103-104). Also available in print.

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Hapuarachchi, Pasan. "Feature selection and artifact removal in sleep stage classification." Thesis, University of Waterloo, 2006. http://hdl.handle.net/10012/2879.

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The use of Electroencephalograms (EEG) are essential to the analysis of sleep disorders in patients. With the use of electroencephalograms, electro-oculograms (EOG), and electromyograms (EMG), doctors and EEG technician can make conclusions about the sleep patterns of patients. In particular, the classification of the sleep data into various stages, such as NREM I-IV, REM, Awake, is extremely important. The EEG signal itself is highly sensitive to physiological and non-physiological artifacts. Trained human experts can accommodate for these artifacts while they are analyzing the EEG si

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Lozano, Vega Gildardo. "Image-based detection and classification of allergenic pollen." Thesis, Dijon, 2015. http://www.theses.fr/2015DIJOS031/document.

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Le traitement médical des allergies nécessite la caractérisation des pollens en suspension dans l’air. Toutefois, cette tâche requiert des temps d’analyse très longs lorsqu’elle est réalisée de manière manuelle. Une approche automatique améliorerait ainsi considérablement les applications potentielles du comptage de pollens. Les dernières techniques d’analyse d’images permettent la détection de caractéristiques discriminantes. C’est pourquoi nous proposons dans cette thèse un ensemble de caractéristiques pertinentes issues d’images pour la reconnaissance des principales classes de pollen aller

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35

Gao, Jiangning. "3D face recognition using multicomponent feature extraction from the nasal region and its environs." Thesis, University of Bath, 2016. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.707585.

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This thesis is dedicated to extracting expression robust features for 3D face recognition. The use of 3D imaging enables the extraction of discriminative features that can significantly improve the recognition performance due to the availability of facial surface information such as depth, surface normals and curvature. Expression robust analysis using information from both depth and surface normals is investigated by dividing the main facial region into patches of different scales. The nasal region and adjoining parts of the cheeks are utilized as they are more consistent over different expre

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36

Malkhare, Rohan V. "Scavenger: A Junk Mail Classification Program." Scholar Commons, 2003. https://scholarcommons.usf.edu/etd/1145.

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The problem of junk mail, also called spam, has reached epic proportions and various efforts are underway to fight spam. Junk mail classification using machine learning techniques is a key method to fight spam. We have devised a machine learning algorithm where features are created from individual sentences in the subject and body of a message by forming all possible word-pairings from a sentence. Weights are assigned to the features based on the strength of their predictive capabilities for spam/legitimate determination. The predictive capabilities are estimated by the frequency of occurrence

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Saidi, Rabie. "Motif extraction from complex data : case of protein classification." Thesis, Clermont-Ferrand 2, 2012. http://www.theses.fr/2012CLF22272/document.

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La classification est l’un des défis important en bioinformatique, aussi bien pour les données protéiques que nucléiques. La présence de ces données en grandes masses, leur ambiguïté et en particulier les coûts élevés de l’analyse in vitro en termes de temps et d’argent, rend l’utilisation de la fouille de données plutôt une nécessité qu’un choix rationnel. Cependant, les techniques fouille de données, qui traitent souvent des données sous le format relationnel, sont confrontés avec le format inapproprié des données biologiques. Par conséquent, une étape inévitable de prétraitement doit être é

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De, Voir Christopher S. "Wavelet Based Feature Extraction and Dimension Reduction for the Classification of Human Cardiac Electrogram Depolarization Waveforms." PDXScholar, 2005. https://pdxscholar.library.pdx.edu/open_access_etds/1740.

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An essential task for a pacemaker or implantable defibrillator is the accurate identification of rhythm categories so that the correct electrotherapy can be administered. Because some rhythms cause a rapid dangerous drop in cardiac output, it is necessary to categorize depolarization waveforms on a beat-to-beat basis to accomplish rhythm classification as rapidly as possible. In this thesis, a depolarization waveform classifier based on the Lifting Line Wavelet Transform is described. It overcomes problems in existing rate-based event classifiers; namely, (1) they are insensitive to the conduc

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PORTO, BUARQUE DE GUSMAO PEDRO. "Feature extraction using MPEG-CDVS and Deep Learning with application to robotic navigation and image classification." Doctoral thesis, Politecnico di Torino, 2017. http://hdl.handle.net/11583/2665943.

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The main contributions of this thesis are the evaluation of MPEG Compact Descriptor for Visual Search in the context of indoor robotic navigation and the introduction of a new method for training Convolutional Neural Networks with applications to object classification. The choice for image descriptor in a visual navigation system is not straightforward. Visual descriptors must be distinctive enough to allow for correct localisation while still offering low matching complexity and short descriptor size for real-time applications. MPEG Compact Descriptor for Visual Search is a low complexity i

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Paradzinets, Aliaksandr V. "Variable resolution transform-based music feature extraction and their applications for music information retrieval." Ecully, Ecole centrale de Lyon, 2007. http://www.theses.fr/2007ECDL0047.

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Dans le secteur de loisirs il y a un nombre considérable d’enregistrements numériques musicaux produits, diffusés et échangés qui favorise la demande croisante de services intelligents de recherche de musique. La navigation par contenu devient cruciale pour permettre aux professionnels et également aux amateurs d’accéder facilement aux quantités de données musicales disponibles. Ce travail présente les nouveaux descripteurs de contenu musical et mesures de similarité qui permettent l’organisation automatique de données musicales (recherche par similarité, génération automatique des playlistes)

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Eklund, Martin. "Comparing Feature Extraction Methods and Effects of Pre-Processing Methods for Multi-Label Classification of Textual Data." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-231438.

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This thesis aims to investigate how different feature extraction methods applied to textual data affect the results of multi-label classification. Two different Bag of Words extraction methods are used, specifically the Count Vector and the TF-IDF approaches. A word embedding method is also investigated, called the GloVe extraction method. Multi-label classification can be useful for categorizing items, such as pieces of music or news articles, that may belong to multiple classes or topics. The effect of using different pre-processing methods is also investigated, such as the use of N-grams, s

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Stromann, Oliver. "Feature Extraction and FeatureSelection for Object-based LandCover Classification : Optimisation of Support Vector Machines in aCloud Computing Environment." Thesis, KTH, Geoinformatik, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-238727.

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Mapping the Earth’s surface and its rapid changes with remotely sensed data is a crucial tool to un-derstand the impact of an increasingly urban world population on the environment. However, the impressive amount of freely available Copernicus data is only marginally exploited in common clas-sifications. One of the reasons is that measuring the properties of training samples, the so-called ‘fea-tures’, is costly and tedious. Furthermore, handling large feature sets is not easy in most image clas-sification software. This often leads to the manual choice of few, allegedly promising features. In

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Salmon, Brian Paxton. "Improved hyper-temporal feature extraction methods for land cover change detection in satellite time series." Thesis, University of Pretoria, 2012. http://hdl.handle.net/2263/28199.

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The growth in global population inevitably increases the consumption of natural resources. The need to provide basic services to these growing communities leads to an increase in anthropogenic changes to the natural environment. The resulting transformation of vegetation cover (e.g. deforestation, agricultural expansion, urbanisation) has significant impacts on hydrology, biodiversity, ecosystems and climate. Human settlement expansion is the most common driver of land cover change in South Africa, and is currently mapped on an irregular, ad hoc basis using visual interpretation of aerial phot

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Koc, Bengi. "Detection And Classification Of Qrs Complexes From The Ecg Recordings." Master's thesis, METU, 2008. http://etd.lib.metu.edu.tr/upload/2/12610328/index.pdf.

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Electrocardiography (ECG) is the most important noninvasive tool used for diagnosing heart diseases. An ECG interpretation program can help the physician state the diagnosis correctly and take the corrective action. Detection of the QRS complexes from the ECG signal is usually the first step for an interpretation tool. The main goal in this thesis was to develop robust and high performance QRS detection algorithms, and using the results of the QRS detection step, to classify these beats according to their different pathologies. In order to evaluate the performances, these algorithms were teste

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陳偉政. "Improve Feature Extraction and Matching Methods for Gesture Identification." Thesis, 2004. http://ndltd.ncl.edu.tw/handle/26495873724164038367.

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碩士<br>中華大學<br>資訊工程學系碩士班<br>92<br>A gesture identification system is proposed in this thesis. For image segmentation, the HSL information of the image is used to find the gesture region, the gray level histogram is applied to determine the threshold for image partition. In feature extraction, an ellipse mask is constructed to determine the features such as the number of fingers, the angles between fingers, the distances between the fingers and the palm, and the curvature of the palm’s contour. In the recognition procedure, a similarity measure is achieved by calculating the distance between fe

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Chiou, Tzone-Kaie, and 邱宗楷. "Using Fuzzy Feature Extraction Fingerprint Classification." Thesis, 2001. http://ndltd.ncl.edu.tw/handle/92760623300716087147.

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碩士<br>元智大學<br>資訊工程學系<br>89<br>Fingerprint classification is a useful task for a large database of fingerprint recognition system. Accurate classification can speed up the process of fingerprint recognition. The fingerprint classification method proposed in this paper is based on human thinking and uses fuzzy theory. The key point of human thinking to classify fingerprint is attempting to find out fingerprint ridge, singular points (cores or deltas), direction of ridge, wrinkles or scars as global features. Firstly, in order to determine the fingerprint ridge direction, we need to transform the

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Jiun-Jin, Huang, and 黃俊錦. "Effects of Feature Extraction on Classification Accuracy." Thesis, 1998. http://ndltd.ncl.edu.tw/handle/86200872473956722918.

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碩士<br>國立臺灣科技大學<br>管理技術研究所<br>86<br>Classification is an important area in pattern recognition. Feature extra ction for classification is equivalent to retaining informative features or eliminating redundant features. However, due to the nonlinearity of the decision boundary, which occurs in most cases, there exist no absolutely but approxima tely redundant features. Eliminating approximately redundant features results in a decrease in the classification accuracy. Even for two classes with multiv ariate normal distributions, classification accuracy is difficult to analyze s ince the classificat

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Lin, Chia-Hsing, and 林家興. "Discriminative Feature Extraction for Robust Audio Event Classification." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/4v582f.

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碩士<br>國立臺北科技大學<br>電腦與通訊研究所<br>98<br>In Tradition, audio event classification relies heavily on MFCCs (Mel-Frequency Cepstral Coefficients) features. However, MFCCs is originally designed for automatic speech recognition. It is not sure whether MFCCs are still the best features for audio event classification or not. Besides, MFCCs are usually not so robust in noisy environment. Therefore, in this paper, several new feature extraction methods are proposed in the hope of getting better performance and robustness than MFCCs in noisy conditions. The proposed feature extraction methods are main

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Liu, Yu-Hsin, and 劉羽欣. "Feature extraction and classification of product advertising review." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/q67wnd.

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碩士<br>國立臺北科技大學<br>資訊工程系研究所<br>101<br>Web has become an important place for marketing in business. Many vendors offer bloggers or people their products or payment and ask them to write review of product using experience to promote their products. However, it’s hard to identify the truthfulness of these reviews. By using conventional text classification methods by content, it is difficult to distinguish between real and fake reviews. In this paper, we propose a feature extraction method and classification model for advertising reviews. Based on features like ratio of positive opinion terms,

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Liang, Jie. "Spectral-spatial Feature Extraction for Hyperspectral Image Classification." Phd thesis, 2016. http://hdl.handle.net/1885/111995.

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As an emerging technology, hyperspectral imaging provides huge opportunities in both remote sensing and computer vision. The advantage of hyperspectral imaging comes from the high resolution and wide range in the electromagnetic spectral domain which reflects the intrinsic properties of object materials. By combining spatial and spectral information, it is possible to extract more comprehensive and discriminative representation for objects of interest than traditional methods, thus facilitating the basic pattern recognition tasks, such as object detectio

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