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Dissertations / Theses on the topic 'Support Vector Classifier (SVC)'

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Published: 5 June 2025

Last updated: 2 August 2025

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1

Reyaz-Ahmed, Anjum B. "Protein Secondary Structure Prediction Using Support Vector Machines, Nueral Networks and Genetic Algorithms." Digital Archive @ GSU, 2007. http://digitalarchive.gsu.edu/cs_theses/43.

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Bioinformatics techniques to protein secondary structure prediction mostly depend on the information available in amino acid sequence. Support vector machines (SVM) have shown strong generalization ability in a number of application areas, including protein structure prediction. In this study, a new sliding window scheme is introduced with multiple windows to form the protein data for training and testing SVM. Orthogonal encoding scheme coupled with BLOSUM62 matrix is used to make the prediction. First the prediction of binary classifiers using multiple windows is compared with single window

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Shantilal. "SUPPORT VECTOR MACHINE FOR HIGH THROUGHPUT RODENT SLEEP BEHAVIOR CLASSIFICATION." UKnowledge, 2008. http://uknowledge.uky.edu/gradschool_theses/506.

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This thesis examines the application of a Support Vector Machine (SVM) classifier to automatically detect sleep and quiet wake (rest) behavior in mice from pressure signals on their cage floor. Previous work employed Neural Networks (NN) and Linear Discriminant Analysis (LDA) to successfully detect sleep and wake behaviors in mice. Although the LDA was successful in distinguishing between the sleep and wake behaviors, it has several limitations, which include the need to select a threshold and difficulty separating additional behaviors with subtle differences, such as sleep and rest. The SVM h

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Beltrami, Monica. "Método Grid-Quadtree para seleção de parâmetros do algoritmo support vector classification (SVC)." reponame:Repositório Institucional da UFPR, 2016. http://hdl.handle.net/1884/44061.

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Orientador : Prof. Dr. Arinei Carlos Lindbeck da Silva<br>Tese (doutorado) - Universidade Federal do Paraná, Setor de Tecnologia, Programa de Pós-Graduação em Métodos Numéricos em Engenharia. Defesa: Curitiba, 01/06/2016<br>Inclui referências : f. 143-149<br>Área de concentração : Programação matemática<br>Resumo: O algoritmo Support Vector Classification (SVC) é uma técnica de reconhecimento de padrões, cuja eficiência depende da seleção de seus parâmetros: constante de regularização C, função kernel e seus respectivos parâmetros. A escolha equivocada dessas variáveis impacta diretamente na p

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WANDEKOKEN, E. D. "Support Vector Machine Ensemble Based on Feature and Hyperparameter Variation." Universidade Federal do Espírito Santo, 2011. http://repositorio.ufes.br/handle/10/4234.

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Made available in DSpace on 2016-08-29T15:33:14Z (GMT). No. of bitstreams: 1 tese_4163_.pdf: 479699 bytes, checksum: 04f01a137084c0859b4494de6db8b3ac (MD5) Previous issue date: 2011-02-23<br>Classificadores do tipo máquina de vetores de suporte (SVM) são atualmente considerados uma das técnicas mais poderosas para se resolver problemas de classificação com duas classes. Para aumentar o desempenho alcançado por classificadores SVM individuais, uma abordagem bem estabelecida é usar uma combinação de SVMs, a qual corresponde a um conjunto de classificadores SVMs que são, simultaneamente,

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Lai, Guojun, and Bing Li. "Handwritten Document Binarization Using Deep Convolutional Features with Support Vector Machine Classifier." Thesis, Blekinge Tekniska Högskola, Institutionen för datavetenskap, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-20090.

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Background. Since historical handwritten documents have played important roles in promoting the development of human civilization, many of them have been preserved through digital versions for more scientific researches. However, various degradations always exist in these documents, which could interfere in normal reading. But, binarized versions can keep meaningful contents without degradations from original document images. Document image binarization always works as a pre-processing step before complex document analysis and recognition. It aims to extract texts from a document image. A desi

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Venkatachari, Sidhaarth. "Application of Neural Networks to Inverter-Based Resources." Thesis, Virginia Tech, 2021. http://hdl.handle.net/10919/103376.

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With the deployment of sensors in hardware equipment and advanced metering infrastructure, system operators have access to unprecedented amounts of data. Simultaneously, grid-connected power electronics technology has had a large impact on the way electrical energy is generated, transmitted, and delivered to consumers. Artificial intelligence and machine learning can help address the new power grid challenges with enhanced computational abilities and access to large amounts of data. This thesis discusses the fundamentals of neural networks and their applications in power systems such as load f

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Abo, Al Ahad George, and Abbas Salami. "Machine Learning for Market Prediction : Soft Margin Classifiers for Predicting the Sign of Return on Financial Assets." Thesis, Linköpings universitet, Produktionsekonomi, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-151459.

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Forecasting procedures have found applications in a wide variety of areas within finance and have further shown to be one of the most challenging areas of finance. Having an immense variety of economic data, stakeholders aim to understand the current and future state of the market. Since it is hard for a human to make sense out of large amounts of data, different modeling techniques have been applied to extract useful information from financial databases, where machine learning techniques are among the most recent modeling techniques. Binary classifiers such as Support Vector Machines (SVMs) h

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Amlathe, Prakhar. "Standard Machine Learning Techniques in Audio Beehive Monitoring: Classification of Audio Samples with Logistic Regression, K-Nearest Neighbor, Random Forest and Support Vector Machine." DigitalCommons@USU, 2018. https://digitalcommons.usu.edu/etd/7050.

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Honeybees are one of the most important pollinating species in agriculture. Every three out of four crops have honeybee as their sole pollinator. Since 2006 there has been a drastic decrease in the bee population which is attributed to Colony Collapse Disorder(CCD). The bee colonies fail/ die without giving any traditional health symptoms which otherwise could help in alerting the Beekeepers in advance about their situation. Electronic Beehive Monitoring System has various sensors embedded in it to extract video, audio and temperature data that could provide critical information on colony beha

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Naram, Hari Prasad. "Classification of Dense Masses in Mammograms." OpenSIUC, 2018. https://opensiuc.lib.siu.edu/dissertations/1528.

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This dissertation material provided in this work details the techniques that are developed to aid in the Classification of tumors, non-tumors, and dense masses in a Mammogram, certain characteristics such as texture in a mammographic image are used to identify the regions of interest as a part of classification. Pattern recognizing techniques such as nearest mean classifier and Support vector machine classifier are also used to classify the features. The initial stages include the processing of mammographic image to extract the relevant features that would be necessary for classification and d

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Xia, Junshi. "Multiple classifier systems for the classification of hyperspectral data." Thesis, Grenoble, 2014. http://www.theses.fr/2014GRENT047/document.

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Dans cette thèse, nous proposons plusieurs nouvelles techniques pour la classification d'images hyperspectrales basées sur l'apprentissage d'ensemble. Le cadre proposé introduit des innovations importantes par rapport aux approches précédentes dans le même domaine, dont beaucoup sont basées principalement sur un algorithme individuel. Tout d'abord, nous proposons d'utiliser la Forêt de Rotation (Rotation Forest) avec différentes techiniques d'extraction de caractéristiques linéaire et nous comparons nos méthodes avec les approches d'ensemble traditionnelles, tels que Bagging, Boosting, Sous-es

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Michel, David. "All Negative on the Western Front: Analyzing the Sentiment of the Russian News Coverage of Sweden with Generic and Domain-Specific Multinomial Naive Bayes and Support Vector Machines Classifiers." Thesis, Uppsala universitet, Institutionen för lingvistik och filologi, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-447398.

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This thesis explores to what extent Multinomial Naive Bayes (MNB) and Support Vector Machines (SVM) classifiers can be used to determine the polarity of news, specifically the news coverage of Sweden by the Russian state-funded news outlets RT and Sputnik. Three experiments are conducted. In the first experiment, an MNB and an SVM classifier are trained with the Large Movie Review Dataset (Maas et al., 2011) with a varying number of samples to determine how training data size affects classifier performance. In the second experiment, the classifiers are trained with 300 positive, negative, an

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Chen, Xiujuan. "Computational Intelligence Based Classifier Fusion Models for Biomedical Classification Applications." Digital Archive @ GSU, 2007. http://digitalarchive.gsu.edu/cs_diss/26.

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The generalization abilities of machine learning algorithms often depend on the algorithms’ initialization, parameter settings, training sets, or feature selections. For instance, SVM classifier performance largely relies on whether the selected kernel functions are suitable for real application data. To enhance the performance of individual classifiers, this dissertation proposes classifier fusion models using computational intelligence knowledge to combine different classifiers. The first fusion model called T1FFSVM combines multiple SVM classifiers through constructing a fuzzy logic system.

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Fonseca, Everthon Silva. "Wavelets, predição linear e LS-SVM aplicados na análise e classificação de sinais de vozes patológicas." Universidade de São Paulo, 2008. http://www.teses.usp.br/teses/disponiveis/18/18133/tde-04072008-094655/.

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Neste trabalho, foram utilizadas as vantagens da ferramenta matemática de análise temporal e espectral, a transformada wavelet discreta (DWT), além dos coeficientes de predição linear (LPC) e do algoritmo de inteligência artificial, Least Squares Support Vector Machines (LS-SVM), para aplicações em análise de sinais de voz e classificação de vozes patológicas. Inúmeros trabalhos na literatura têm demonstrado o grande interesse existente por ferramentas auxiliares ao diagnóstico de patologias da laringe. Os componentes da DWT forneceram parâmetros de medida para a análise e classificação das vo

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Hu, Hae-Jin. "Design of Comprehensible Learning Machine Systems for Protein Structure Prediction." Digital Archive @ GSU, 2007. http://digitalarchive.gsu.edu/cs_diss/22.

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With the efforts to understand the protein structure, many computational approaches have been made recently. Among them, the Support Vector Machine (SVM) methods have been recently applied and showed successful performance compared with other machine learning schemes. However, despite the high performance, the SVM approaches suffer from the problem of understandability since it is a black-box model; the predictions made by SVM cannot be interpreted as biologically meaningful way. To overcome this limitation, a new association rule based classifier PCPAR was devised based on the existing cla

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Dočekal, Martin. "Porovnání klasifikačních metod." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2019. http://www.nusl.cz/ntk/nusl-403211.

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This thesis deals with a comparison of classification methods. At first, these classification methods based on machine learning are described, then a classifier comparison system is designed and implemented. This thesis also describes some classification tasks and datasets on which the designed system will be tested. The evaluation of classification tasks is done according to standard metrics. In this thesis is presented design and implementation of a classifier that is based on the principle of evolutionary algorithms.

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Soares, Heliana Bezerra. "An?lise e classifica??o de imagens de les?es da pele por atributos de cor, forma e textura utilizando m?quina de vetor de suporte." Universidade Federal do Rio Grande do Norte, 2008. http://repositorio.ufrn.br:8080/jspui/handle/123456789/15118.

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Made available in DSpace on 2014-12-17T14:54:49Z (GMT). No. of bitstreams: 1 HelianaBS_da_capa_ate_cap4.pdf: 2361373 bytes, checksum: 3e1e43e8ba1aadc274663b8b8e3de72f (MD5) Previous issue date: 2008-02-22<br>Conselho Nacional de Desenvolvimento Cient?fico e Tecnol?gico<br>The skin cancer is the most common of all cancers and the increase of its incidence must, in part, caused by the behavior of the people in relation to the exposition to the sun. In Brazil, the non-melanoma skin cancer is the most incident in the majority of the regions. The dermatoscopy and videodermatoscopy are the main

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Ngo, Ho Anh Khoi. "Méthodes de classifications dynamiques et incrémentales : application à la numérisation cognitive d'images de documents." Thesis, Tours, 2015. http://www.theses.fr/2015TOUR4006/document.

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Cette thèse s’intéresse à la problématique de la classification dynamique en environnements stationnaires et non stationnaires, tolérante aux variations de quantités des données d’apprentissage et capable d’ajuster ses modèles selon la variabilité des données entrantes. Pour cela, nous proposons une solution faisant cohabiter des classificateurs one-class SVM indépendants ayant chacun leur propre procédure d’apprentissage incrémentale et par conséquent, ne subissant pas d’influences croisées pouvant émaner de la configuration des modèles des autres classificateurs. L’originalité de notre propo

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Caujolle, Mathieu. "Identification et caractérisation des perturbations affectant les réseaux électriques HTA." Phd thesis, Supélec, 2011. http://tel.archives-ouvertes.fr/tel-00650911.

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La reconnaissance des perturbations survenant sur les réseaux HTA est une problématique essentielle pour les clients industriels comme pour le gestionnaire du réseau. Ces travaux de thèse ont permis de développer un système d'identification automatique. Il s'appuie sur des méthodes de segmentation qui décomposent de manière précise et efficace les régimes transitoires et permanents des perturbations. Elles utilisent des filtres de types Kalman linéaire ou anti-harmoniques pour extraire les régimes transitoires. La prise en compte des variations harmoniques et de la présence de transitoires pro

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Vuk, Vranjković. "Реконфигурабилне архитектуре за хардверску акцелерацију предиктивних модела машинског учења". Phd thesis, Univerzitet u Novom Sadu, Fakultet tehničkih nauka u Novom Sadu, 2015. http://www.cris.uns.ac.rs/record.jsf?recordId=94819&source=NDLTD&language=en.

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У овој дисертацији представљене су универзалне реконфигурабилнеархитектуре грубог степена гранулације за хардверску имплементацијуDT (decision trees), ANN (artificial neural networks) и SVM (support vectormachines) предиктивних модела као и хомогених и хетерогенихансамбала. Коришћењем ових архитектура реализоване су две врстеDT модела, две врсте ANN модела, две врсте SVM модела и седамврста ансамбала на FPGA (field programmable gate arrays) чипу.Експерименти, засновани на скуповима из стандардне UCI базе скуповаза машинско учење, показују да FPGA имплементација омогућавазначајно убрзање (од 1

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LOPES, Marcus Vinicius de Sousa. "Aplicação de classificadores para determinação de conformidade de biodiesel." Universidade Federal do Maranhão, 2017. http://tedebc.ufma.br:8080/jspui/handle/tede/1896.

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Submitted by Rosivalda Pereira (mrs.pereira@ufma.br) on 2017-09-04T17:47:07Z No. of bitstreams: 1 MarcusLopes.pdf: 2085041 bytes, checksum: 14f6f9bbe0d5b050a23103874af8c783 (MD5)<br>Made available in DSpace on 2017-09-04T17:47:07Z (GMT). No. of bitstreams: 1 MarcusLopes.pdf: 2085041 bytes, checksum: 14f6f9bbe0d5b050a23103874af8c783 (MD5) Previous issue date: 2017-07-26<br>The growing demand for energy and the limitations of oil reserves have led to the search for renewable and sustainable energy sources to replace, even partially, fossil fuels. Biodiesel has become in last decades the ma

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Xavier, Clahildek Matos. "Segmentação, classificação e quantificação de bacilos de tuberculose em imagens de baciloscopia de campo claro através do emprego de uma nova técnica de classificação de pixels utilizando máquinas de vetores de suporte." Universidade Federal do Amazonas, 2012. http://tede.ufam.edu.br/handle/tede/4387.

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Submitted by Geyciane Santos (geyciane_thamires@hotmail.com) on 2015-07-15T14:04:04Z No. of bitstreams: 1 Dissertação - Clahildek Matos Xavier.pdf: 23017599 bytes, checksum: f3e0230fd866c0a784966606404bb807 (MD5)<br>Approved for entry into archive by Divisão de Documentação/BC Biblioteca Central (ddbc@ufam.edu.br) on 2015-07-15T18:37:45Z (GMT) No. of bitstreams: 1 Dissertação - Clahildek Matos Xavier.pdf: 23017599 bytes, checksum: f3e0230fd866c0a784966606404bb807 (MD5)<br>Approved for entry into archive by Divisão de Documentação/BC Biblioteca Central (ddbc@ufam.edu.br) on 2015-07-15T18:47:

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Nguyen, Van Toi. "Visual interpretation of hand postures for human-machine interaction." Thesis, La Rochelle, 2015. http://www.theses.fr/2015LAROS035/document.

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Aujourd'hui, les utilisateurs souhaitent interagir plus naturellement avec les systèmes numériques. L'une des modalités de communication la plus naturelle pour l'homme est le geste de la main. Parmi les différentes approches que nous pouvons trouver dans la littérature, celle basée sur la vision est étudiée par de nombreux chercheurs car elle ne demande pas de porter de dispositif complémentaire. Pour que la machine puisse comprendre les gestes à partir des images RGB, la reconnaissance automatique de ces gestes est l'un des problèmes clés. Cependant, cette approche présente encore de multiple

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Maršánová, Lucie. "Analýza experimentálních EKG záznamů." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2015. http://www.nusl.cz/ntk/nusl-221365.

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This diploma thesis deals with the analysis of experimental electrograms (EG) recorded from isolated rabbit hearts. The theoretical part is focused on the basic principles of electrocardiography, pathological events in ECGs, automatic classification of ECG and experimental cardiological research. The practical part deals with manual classification of individual pathological events – these results will be presented in the database of EG records, which is under developing at the Department of Biomedical Engineering at BUT nowadays. Manual scoring of data was discussed with experts. After that, t

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Skogsmo, Markus. "A Scalable Approach for Detecting Dumpsites using Automatic Target Recognition with Feature Selection and SVM through Satellite Imagery." Thesis, Uppsala universitet, Avdelningen för visuell information och interaktion, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-418792.

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Throughout the world, there is a great demand to map out the increasing environmental changes and life habitats on Earth. The vast majority of Earth Observations today, are collected using satellites. The Global Watch Center (GWC) initiative was started with the purpose of producing a global situational awareness of the premises for all life on Earth. By collecting, studying and analyzing vast amounts of data in an automatic, scalable and transparent way, the GWC aims are to work towards reaching the United Nations (UN) Sustainable Development Goals (SDG). The GWC vision is to make use of qual

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Veľas, Martin. "Automatické třídění fotografií podle obsahu." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2013. http://www.nusl.cz/ntk/nusl-236399.

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This thesis deals with content based automatic photo categorization. The aim of the work is to experiment with advanced techniques of image represenatation and to create a classifier which is able to process large image dataset with sufficient accuracy and computation speed. A traditional solution based on using visual codebooks is enhanced by computing color features, soft assignment of visual words to extracted feature vectors, usage of image segmentation in process of visual codebook creation and dividing picture into cells. These cells are processed separately. Linear SVM classifier with e

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"A Semantic Triplet Based Story Classifier." Master's thesis, 2013. http://hdl.handle.net/2286/R.I.17802.

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abstract: Text classification, in the artificial intelligence domain, is an activity in which text documents are automatically classified into predefined categories using machine learning techniques. An example of this is classifying uncategorized news articles into different predefined categories such as "Business", "Politics", "Education", "Technology" , etc. In this thesis, supervised machine learning approach is followed, in which a module is first trained with pre-classified training data and then class of test data is predicted. Good feature extraction is an important step in the machine

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Bapat, Tanuja. "Sparse Multiclass And Multi-Label Classifier Design For Faster Inference." Thesis, 2011. https://etd.iisc.ac.in/handle/2005/2065.

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Many real-world problems like hand-written digit recognition or semantic scene classiﬁcation are treated as multiclass or multi-label classiﬁcation prob-lems. Solutions to these problems using support vector machines (SVMs) are well studied in literature. In this work, we focus on building sparse max-margin classiﬁers for multiclass and multi-label classiﬁcation. Sparse representation of the resulting classiﬁer is important both from eﬃcient training and fast inference viewpoints. This is true especially when the training and test set sizes are large.Very few of the existing multiclass and mul

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Bapat, Tanuja. "Sparse Multiclass And Multi-Label Classifier Design For Faster Inference." Thesis, 2011. http://etd.iisc.ernet.in/handle/2005/2065.

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Many real-world problems like hand-written digit recognition or semantic scene classiﬁcation are treated as multiclass or multi-label classiﬁcation prob-lems. Solutions to these problems using support vector machines (SVMs) are well studied in literature. In this work, we focus on building sparse max-margin classiﬁers for multiclass and multi-label classiﬁcation. Sparse representation of the resulting classiﬁer is important both from eﬃcient training and fast inference viewpoints. This is true especially when the training and test set sizes are large.Very few of the existing multiclass and mul

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Hembram, Rajkishore. "Study on support vector machine as a classifier." Thesis, 2011. http://ethesis.nitrkl.ac.in/2603/1/Raka_thesis.pdf.

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SVM [1], [2] is a learning method which learns by considering data points to be in space. We studied different types of Support Vector Machine (SVM). We also observed their classification process. We conducted10-fold testing experiments on LSSVM [7], [8] (Least square Support Vector Machine) and PSVM [9] (Proximal Support Vector Machine) using standard sets of data. Finally we proposed a new algorithm NPSVM (Non-Parallel Support Vector Machine) which is reformulated from NPPC [12], [13] (Non-Parallel Plane Classifier). We have observed that the cost function of NPPC is affected by the ad

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Lin, Yu-li, and 林育利. "Using Neural Networks with Support Vector Machines to Classifier." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/3p5w55.

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碩士<br>國立中央大學<br>光機電工程研究所<br>96<br>Several studies have been reported on the characteristics of data sets which are directly correlated with the capability of the classifier. Therefore, a study in the cognition is conceived, and we suggest the feature optimization to guarantee class separability. We present that the available resource of feature extraction concepts of neural networks(NN) can be applied to the feature optimization problem. Thus, we propose the NN-SVM to set a sufficient number of features compensating for the lack of information. In the NN-SVM algorithm, we use the NN to t

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Oraon, Deepika. "Study on proximal support vector machine as a classifier." Thesis, 2012. http://ethesis.nitrkl.ac.in/4052/1/210ec3326.pdf.

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Proximal Support Vector machine based on Least Mean Square Algorithm classi-fiers (LMS-SVM) are tools for classification of binary data. Proximal Support Vector based on Least Mean Square Algorithm classifiers is completely based on the theory of Proximal Support Vector Machine classifiers (PSVM). PSVM classifies binary pat- terns by assigning them to the closest of two parallel planes that are pushed apart as far as possible. The training time for the classifier is found to be faster compared to their previous versions of Support Vector Machines. But due to the presence of slack variable or

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Shendre, Kanchan. "Intrusion Detection Using Honeypot and Support Vector Machine Classifier." Thesis, 2015. http://ethesis.nitrkl.ac.in/7997/1/672.pdf.

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The rapid growth of internet and web based applications has given rise to the number of attacks on the network. The way the attacker attacks the system differs from one attacker to the other. The sequence of attack or the signature of an attacker should be stored, analyzed and used to generate rules for mitigating future attack attempts. We have deployed honeypot to record the activities of the attacker. While the attacker prepares for an attack, the IDS redirects him to the honeypot. We make the attacker believe that he is working with the actual system. The activities related to the attack a

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Yu-AnnChen and 陳昱安. "Local Learning for Support Vector Classifier and Radial Basis Function Regressor." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/9555c6.

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Chen-Hao and 吳振豪. "Independent Component analysis and Support Vector Classifier Machine for Brain volume analysis." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/38235369702489764528.

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碩士<br>中山醫學大學<br>醫學研究所<br>96<br>Purpose: This research aimed to combine a support vector classifier machine with independent component analysis, without additional image, to effectively and accurately evaluate brain volume. This way, we could obtain more information for diagnosis. Background: Previously we have dealt with software in brain imaging in which Statistical Parametric Mapping is the international standard. However, before calculations, we must add and perform T1-weighted 3D MP-range images so this software can be accepted. So, without adding or running these prerequisite images be

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Li, Chun-Hsien, and 李俊賢. "The Application of Support Vector Machine Classifier to Cultured Customer Electricity Theft." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/52973621956292157264.

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碩士<br>國立高雄應用科技大學<br>電機工程系博碩士班<br>96<br>This thesis proposes support vector machine based pattern recognition technique to classify cultured customer electricity theft by establishing and comparing with the various rational load patterns. First, in this research, Taiwan western coach cultured customers’ historical electricity data is collected and analyzed to derive summer and non-summer rational daily load patterns. Moreover, SVM network model is applied to train the selected cultured customer data set to establish the cultured customer electricity theft classifier and then the electricity the

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Cheng, Yuen-Tse, and 鄭淵澤. "The Application of Support Vector Machine Classifier to Commercial Customer Electricity Theft." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/71035570493855375880.

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碩士<br>國立高雄應用科技大學<br>電機工程系<br>98<br>This thesis proposes support vector machine based pattern recognition technique to classify commercial customer electricity theft by establishing and comparing with the various rational load patterns. First, in this thesis, Taiwan commercial customers’ historical electricity data is collected to derive the summer and non-summer reasonable power consumption model. Moreover, the SVM network model is employed to train the selected commercial customer data set to establish the commercial customer electricity theft classifier and then the electricity theft electri

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Chen, Kuan-Ting, and 陳冠廷. "The Comparison of Support Vector Machine and Softmax Classifier in Butterflies Recognition Problem." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/93g7ka.

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碩士<br>國立中央大學<br>數學系<br>107<br>The purpose of this thesis is to explore the training resul ts of two deep learning models ：(1) Support Vector Machine ；(2) Softmax Classifier in image recognition, and study the influence of loss functions on the iterative parameters . We demonstrate the results of these two models by use of the image s of butterflies. There are five types of butterflies with 8214 pictures obtained through the onlin e database website. We use these pictures for the files of data samples to two deep learning models, and observe the training time and accuracy. Next, we analyze the

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Candra, Henry. "Emotion recognition using facial expression and electroencephalography features with support vector machine classifier." Thesis, 2017. http://hdl.handle.net/10453/116427.

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University of Technology Sydney. Faculty of Engineering and Information Technology.<br>Recognizing emotions from facial expression and electroencephalography (EEG) emotion signals are complicated tasks that require substantial issues to be solved in order to achieve higher performance of the classifications, i.e. facial expression has to deal with features, features dimensionality, and classification processing time, while EEG emotion recognition has the concerned with features, number of channels and sub band frequency, and also non-stationary behaviour of EEG signals. This thesis addresses t

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Leu, Chun-Liang, and 呂俊良. "Optimization Algorithms Design for Support Vector Machine Classifier and Flexible Job-shop Scheduling Problem." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/93096301380273676546.

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博士<br>淡江大學<br>電機工程學系博士班<br>97<br>In this dissertation, two types of single-objective hybrid model are proposed to improve the classification rate for Support Vector Machine (SVM) classifier and two effective multi-objective optimization algorithms are developed to solve Flexible Job-shop Scheduling Problems (FJSP). In the optimization design for SVM classifier, an order-independent algorithm for the data reduction, called the Dynamic Condensed Nearest Neighbor (DCNN) rule, is proposed to adaptively construct prototypes in training dataset and to reduce the redundant or noisy instances in a cla

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Hung-HsiangChang and 張閎翔. "A novel Support Vector Machines classifier model with Monotonicity Constraints for mining Classification Knowledge." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/90447833788054923459.

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碩士<br>國立成功大學<br>工業與資訊管理學系碩博士班<br>100<br>Data mining techniques support us to find out the hidden patterns and to extract valuable knowledge from databases. With the process of the time, more and more data mining methods have been successively proposed and widely discussed. Support vector machine (SVM) is a state-of-the-art artificial neural network (ANN) based on statistical learning. SVM has been widely applied in many fields, such as credit rating, forecasting corporate financial distress, consumer loan evaluation, text categorization, handwriting recognition, speaker verification, and bioin

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Schmidt, Tino Böhme Hans-Joachim. "Entwicklung einer Methode zur Bestimmung der Relevanz von Klassifikationsmerkmalen bei der Least Square Support Vector Classification (LS-SVC) /." 2007. http://www.gbv.de/dms/ilmenau/abs/555488594schmi.txt.

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Yang, Tang-chun, and 楊棠鈞. "Implementation of a Road Sign Recognition System Based on Integration of Adaboost Classifier and Support Vector Machine." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/28850598979480975307.

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碩士<br>國立成功大學<br>工程科學系碩博士班<br>97<br>Many different automatic technologies have been used to develop driver assistance systems for improving the safety of driving. Road sign recognition system is an important subsystem of a driver assistance system. It can be used to provide the driver about the road sign information in front of the vehicle. In this thesis, a road sign recognition system was proposed which combined Adaboost classifier and support vector machine(SVM) to do the road sign detection and the content recognition, respectively. In the content representation phase, the Canny edge detect

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Sharma, Govind. "Sentiment-Driven Topic Analysis Of Song Lyrics." Thesis, 2012. https://etd.iisc.ac.in/handle/2005/2472.

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Sentiment Analysis is an area of Computer Science that deals with the impact a document makes on a user. The very field is further sub-divided into Opinion Mining and Emotion Analysis, the latter of which is the basis for the present work. Work on songs is aimed at building affective interactive applications such as music recommendation engines. Using song lyrics, we are interested in both supervised and unsupervised analyses, each of which has its own pros and cons. For an unsupervised analysis (clustering), we use a standard probabilistic topic model called Latent Dirichlet Allocation (LDA

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Sharma, Govind. "Sentiment-Driven Topic Analysis Of Song Lyrics." Thesis, 2012. http://etd.iisc.ernet.in/handle/2005/2472.

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Sentiment Analysis is an area of Computer Science that deals with the impact a document makes on a user. The very field is further sub-divided into Opinion Mining and Emotion Analysis, the latter of which is the basis for the present work. Work on songs is aimed at building affective interactive applications such as music recommendation engines. Using song lyrics, we are interested in both supervised and unsupervised analyses, each of which has its own pros and cons. For an unsupervised analysis (clustering), we use a standard probabilistic topic model called Latent Dirichlet Allocation (LDA)

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Santos, Luís Duque. "GPU Accelerated Classifier Benchmarking for Wildfire Related Tasks." Master's thesis, 2018. http://hdl.handle.net/10362/61547.

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Forest fires cause devastating amounts of damage generating negative consequences in the economy, the environment, the populations’ quality of life and in worst case the loss of lives. Having this in mind, the quick and timely prediction of forest fires is a major factor in the mitigation or even negation of the aforementioned consequences. Remote sensing is the process of obtaining information about an object or phenomena without direct interaction. This is the premise on which satellites acquire data of planet Earth. These observations produce enormous amounts of data on a daily basis.

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Metz, Annekatrin. "An Advanced System for the Targeted Classification of Grassland Types with Multi-Temporal SAR Imagery." Doctoral thesis, 2016. https://repositorium.ub.uni-osnabrueck.de/handle/urn:nbn:de:gbv:700-2016100515067.

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In the light of the ongoing loss of biodiversity at the global scale, monitoring grasslands is nowadays of utmost importance considering their functional relevance in terms of the ecosystem services that they provide. Here, guidelines of the European Union like the Fauna-Flora-Habitat Directive and the European Agricultural fund for Rural Development with its HNV indicators are crucial. Indeed, they form the legal framework for nature conservation and define grasslands as one of their conservation targets, whose status needs to be assessed and reported by all member states on a regular basis.

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Pham, Tung Huy. "Some problems in high dimensional data analysis." 2010. http://repository.unimelb.edu.au/10187/8399.

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The bloom of economics and technology has had an enormous impact on society. Along with these developments, human activities nowadays produce massive amounts of data that can be easily collected for relatively low cost with the aid of new technologies. Many examples can be mentioned here including data from web term-document data, sensor arrays, gene expression, finance data, imaging and hyperspectral analysis. Because of the enormous amount of data from various different and new sources, more and more challenging scientific problems appear. These problems have changed the types of problems wh

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"The Detection of Reliability Prediction Cues in Manufacturing Data from Statistically Controlled Processes." Doctoral diss., 2011. http://hdl.handle.net/2286/R.I.9289.

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abstract: Many products undergo several stages of testing ranging from tests on individual components to end-item tests. Additionally, these products may be further "tested" via customer or field use. The later failure of a delivered product may in some cases be due to circumstances that have no correlation with the product's inherent quality. However, at times, there may be cues in the upstream test data that, if detected, could serve to predict the likelihood of downstream failure or performance degradation induced by product use or environmental stresses. This study explores the use of down

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Τσιλιγκιρίδης, Βασίλειος. "Σύγχρονες τεχνικές στις διεπαφές ανθρώπινου εγκεφάλου - υπολογιστή". Thesis, 2011. http://nemertes.lis.upatras.gr/jspui/handle/10889/4399.

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Τα συστήματα διεπαφών ανθρώπινου εγκεφάλου-υπολογιστή (BCIs: Brain-Computer Interfaces) απαιτούν την πραγματικού χρόνου, αποτελεσματική επεξεργασία των μετρήσεων των ηλεκτροεγκεφαλογραφικών (ΗΕΓ) σημάτων του χρήστη τους, προκειμένου να μεταφράσουν τις νοητικές διεργασίες/προθέσεις του σε σήματα ελέγχου εξωτερικών διατάξεων ή συστημάτων. Στο πλαίσιο της εργασίας αυτής μελετήθηκε το θεωρητικό υπόβαθρο του προβλήματος και αναλύθηκαν συνοπτικά οι κυριότερες τεχνικές που χρησιμοποιούνται σήμερα. Επιπρόσθετα, παρουσιάστηκε μία μέθοδος ταξινόμησης των νοητικών προθέσεων της αριστερής και δεξιάς κίνησ

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Mohammadi, Mahnaz. "An Accelerator for Machine Learning Based Classifiers." Thesis, 2017. http://etd.iisc.ac.in/handle/2005/4245.

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Artificial Neural Networks (ANNs) are algorithmic techniques that simulate biological neural systems. Typical realization of ANNs are software solutions using High Level Languages (HLLs) such as C, C++, etc. Such solutions have performance limitations which can be attributed to one of the following reasons: • Code generated by the compiler cannot perform application specific optimizations. • Communication latencies between processors through a memory hierarchy could be significant due to non-deterministic nature of the communications. In data mining _eld, ANN algorithms have been widely used

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