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Dissertations / Theses on the topic 'Hidden Markov support vector machine'

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1

Fu, Teng. "IntelliChair : a non-intrusive sitting posture and sitting activity recognition system." Thesis, Abertay University, 2015. https://rke.abertay.ac.uk/en/studentTheses/5b60a500-c3fc-4a79-9028-d7909e01b78c.

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Current Ambient Intelligence and Intelligent Environment research focuses on the interpretation of a subject’s behaviour at the activity level by logging the Activity of Daily Living (ADL) such as eating, cooking, etc. In general, the sensors employed (e.g. PIR sensors, contact sensors) provide low resolution information. Meanwhile, the expansion of ubiquitous computing allows researchers to gather additional information from different types of sensor which is possible to improve activity analysis. Based on the previous research about sitting posture detection, this research attempts to furthe
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2

Caceres, Carlos Antonio. "Machine Learning Techniques for Gesture Recognition." Thesis, Virginia Tech, 2014. http://hdl.handle.net/10919/52556.

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Classification of human movement is a large field of interest to Human-Machine Interface researchers. The reason for this lies in the large emphasis humans place on gestures while communicating with each other and while interacting with machines. Such gestures can be digitized in a number of ways, including both passive methods, such as cameras, and active methods, such as wearable sensors. While passive methods might be the ideal, they are not always feasible, especially when dealing in unstructured environments. Instead, wearable sensors have gained interest as a method of gesture classifica
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Landry, Matthew. "Analysis of Nanopore Detector Measurements using Machine Learning Methods, with Application to Single-Molecule Kinetics." ScholarWorks@UNO, 2007. http://scholarworks.uno.edu/td/533.

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At its core, a nanopore detector has a nanometer-scale biological membrane across which a voltage is applied. The voltage draws a DNA molecule into an á-hemolysin channel in the membrane. Consequently, a distinctive channel current blockade signal is created as the molecule flexes and interacts with the channel. This flexing of the molecule is characterized by different blockade levels in the channel current signal. Previous experiments have shown that a nanopore detector is sufficiently sensitive such that nearly identical DNA molecules were classified successfully using machine learning tech
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Li, Jinyu. "Soft margin estimation for automatic speech recognition." Diss., Atlanta, Ga. : Georgia Institute of Technology, 2008. http://hdl.handle.net/1853/26613.

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Thesis (Ph.D)--Electrical and Computer Engineering, Georgia Institute of Technology, 2009.<br>Committee Chair: Dr. Chin-Hui Lee; Committee Member: Dr. Anthony Joseph Yezzi; Committee Member: Dr. Biing-Hwang (Fred) Juang; Committee Member: Dr. Mark Clements; Committee Member: Dr. Ming Yuan. Part of the SMARTech Electronic Thesis and Dissertation Collection.
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Peng, Yingli. "Improvement of Data Mining Methods on Falling Detection and Daily Activities Recognition." Thesis, Mittuniversitetet, Avdelningen för informations- och kommunikationssystem, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-25521.

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With the growing phenomenon of an aging population, an increasing numberof older people are living alone for domestic and social reasons. Based on thisfact, falling accidents become one of the most important factors in threateningthe lives of the elderly. Therefore, it is necessary to set up an application to de-tect the daily activities of the elderly. However, falling detection is difficult to recognize because the "falling" motion is an instantaneous motion and easy to confuse with others.In this thesis, three data mining methods were employed on wearable sensors' value; first which contain
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Yau, Wai Chee, and waichee@ieee org. "Video Analysis of Mouth Movement Using Motion Templates for Computer-based Lip-Reading." RMIT University. Electrical and Computer Engineering, 2008. http://adt.lib.rmit.edu.au/adt/public/adt-VIT20081209.162504.

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This thesis presents a novel lip-reading approach to classifying utterances from video data, without evaluating voice signals. This work addresses two important issues which are • the efficient representation of mouth movement for visual speech recognition • the temporal segmentation of utterances from video. The first part of the thesis describes a robust movement-based technique used to identify mouth movement patterns while uttering phonemes. This method temporally integrates the video data of each phoneme into a 2-D grayscale image named as a motion template (MT). This is a view-b
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Truong, Arthur. "Analyse du contenu expressif des gestes corporels." Thesis, Evry, Institut national des télécommunications, 2016. http://www.theses.fr/2016TELE0015/document.

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Aujourd’hui, les recherches portant sur le geste manquent de modèles génériques. Les spécialistes du geste doivent osciller entre une formalisation excessivement conceptuelle et une description purement visuelle du mouvement. Nous reprenons les concepts développés par le chorégraphe Rudolf Laban pour l’analyse de la danse classique contemporaine, et proposons leur extension afin d’élaborer un modèle générique du geste basé sur ses éléments expressifs. Nous présentons également deux corpus de gestes 3D que nous avons constitués. Le premier, ORCHESTRE-3D, se compose de gestes pré-segmentés de ch
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Van, Rooy Theodore. "Stochastic time series prediction comparison with Markov and support vector machine models." Diss., Connect to online resource, 2006. http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:1439425.

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9

Okuyucu, Cigdem. "Semantic Classification And Retrieval System For Environmental Sounds." Master's thesis, METU, 2012. http://etd.lib.metu.edu.tr/upload/12615114/index.pdf.

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The growth of multimedia content in recent years motivated the research on audio classification and content retrieval area. In this thesis, a general environmental audio classification and retrieval approach is proposed in which higher level semantic classes (outdoor, nature, meeting and violence) are obtained from lower level acoustic classes (emergency alarm, car horn, gun-shot, explosion, automobile, motorcycle, helicopter, wind, water, rain, applause, crowd and laughter). In order to classify an audio sample into acoustic classes, MPEG-7 audio features, Mel Frequency Cepstral Coefficients
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Fredborg, Johan. "Spam filter for SMS-traffic." Thesis, Linköpings universitet, Institutionen för datavetenskap, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-94161.

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Communication through text messaging, SMS (Short Message Service), is nowadays a huge industry with billions of active users. Because of the huge userbase it has attracted many companies trying to market themselves through unsolicited messages in this medium in the same way as was previously done through email. This is such a common phenomenon that SMS spam has now become a plague in many countries. This report evaluates several established machine learning algorithms to see how well they can be applied to the problem of filtering unsolicited SMS messages. Each filter is mainly evaluated by an
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11

Chen, Li. "Integrative Modeling and Analysis of High-throughput Biological Data." Diss., Virginia Tech, 2010. http://hdl.handle.net/10919/30192.

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Computational biology is an interdisciplinary field that focuses on developing mathematical models and algorithms to interpret biological data so as to understand biological problems. With current high-throughput technology development, different types of biological data can be measured in a large scale, which calls for more sophisticated computational methods to analyze and interpret the data. In this dissertation research work, we propose novel methods to integrate, model and analyze multiple biological data, including microarray gene expression data, protein-DNA interaction data and protein
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Andersson, Maria, Fredrik Gustafsson, Louis St-Laurent, and Donald Prevost. "Recognition of Anomalous Motion Patterns in Urban Surveillance." Linköpings universitet, Reglerteknik, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-93983.

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We investigate the unsupervised K-means clustering and the semi-supervised hidden Markov model (HMM) to automatically detect anomalous motion patterns in groups of people (crowds). Anomalous motion patterns are typically people merging into a dense group, followed by disturbances or threatening situations within the group. The application of K-means clustering and HMM are illustrated with datasets from four surveillance scenarios. The results indicate that by investigating the group of people in a systematic way with different K values, analyze cluster density, cluster quality and changes in c
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Butko, Taras. "Feature selection for multimodal: acoustic event detection." Doctoral thesis, Universitat Politècnica de Catalunya, 2011. http://hdl.handle.net/10803/32176.

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The detection of the Acoustic Events (AEs) naturally produced in a meeting room may help to describe the human and social activity. The automatic description of interactions between humans and environment can be useful for providing: implicit assistance to the people inside the room, context-aware and content-aware information requiring a minimum of human attention or interruptions, support for high-level analysis of the underlying acoustic scene, etc. On the other hand, the recent fast growth of available audio or audiovisual content strongly demands tools for analyzing, indexing, searching a
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Thomas, Rodney H. "Machine Learning for Exploring State Space Structure in Genetic Regulatory Networks." Diss., NSUWorks, 2018. https://nsuworks.nova.edu/gscis_etd/1053.

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Genetic regulatory networks (GRN) offer a useful model for clinical biology. Specifically, such networks capture interactions among genes, proteins, and other metabolic factors. Unfortunately, it is difficult to understand and predict the behavior of networks that are of realistic size and complexity. In this dissertation, behavior refers to the trajectory of a state, through a series of state transitions over time, to an attractor in the network. This project assumes asynchronous Boolean networks, implying that a state may transition to more than one attractor. The goal of this project is to
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Shepard, Samuel Steven. "The Characterization and Utilization of Middle-range Sequence Patterns within the Human Genome." University of Toledo Health Science Campus / OhioLINK, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=mco1271271172.

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16

Jia, Wei. "Image analysis and representation for textile design classification." Thesis, University of Dundee, 2011. https://discovery.dundee.ac.uk/en/studentTheses/c667f279-d7a6-4670-b23e-c9dbe2784266.

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A good image representation is vital for image comparision and classification; it may affect the classification accuracy and efficiency. The purpose of this thesis was to explore novel and appropriate image representations. Another aim was to investigate these representations for image classification. Finally, novel features were examined for improving image classification accuracy. Images of interest to this thesis were textile design images. The motivation of analysing textile design images is to help designers browse images, fuel their creativity, and improve their design efficiency. In rec
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17

Carminati, Lionel. "Détection et suivi d'objets dans les scènes animées : application à la vidéo surveillance." Bordeaux 1, 2006. http://www.theses.fr/2006BOR13190.

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Dans le cadre de cette thèse nous nous sommes intéressés à l'application des outils d'apprentissage statistique aux problèmes d'extraction et de suivi d'objets dans le contexte de la surveillance vidéo par des caméras statiques. Notre étude se déroule en trois phases : la première consiste à détecter l'ensemble des objets en mouvement par l'analyse des variations de luminosité au cours du temps. Nous avons proposé pour cela une méthode de détection de tels objets dans la continuité des travaux de Grimson et Stauffer à la base de la modélisation de la luminance des pixels par des mélanges des l
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Wehmann, Adam. "A Spatial-Temporal Contextual Kernel Method for Generating High-Quality Land-Cover Time Series." The Ohio State University, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=osu1398866264.

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19

Chen, Wei-Chi, and 陳威棋. "Combining Hidden Markov Model and Support Vector Machine for Host-based Anomaly Detection Systems." Thesis, 2006. http://ndltd.ncl.edu.tw/handle/pyy4du.

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碩士<br>國立中央大學<br>資訊管理研究所<br>94<br>Various malicious programs, such as Trojan horse and backdoor, have become popular on the Internet in recent years. More and more automated penetration testing tools appear and now less background knowledge of attack is needed than before. As a result, the responsibility of computer is transferred to the host-based intrusion detection systems. Our research mainly combines Hidden Markov Model and Support Vector Machine and proposes a host-based anomaly detection system under Windows platforms. We use Windows Native Application Interface (API) sequences to establ
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20

Gassend, B., C. W. O'Donnell, W. Thies, A. Lee, Dijk M. van, and S. Devadas. "Secondary Structure Prediction of All-Helical Proteins Using Hidden Markov Support Vector Machines." 2005. http://hdl.handle.net/1721.1/30571.

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Our goal is to develop a state-of-the-art predictor with an intuitive and biophysically-motivated energy model through the use of Hidden Markov Support Vector Machines (HM-SVMs), a recent innovation in the field of machine learning. We focus on the prediction of alpha helices in proteins and show that using HM-SVMs, a simple 7-state HMM with 302 parameters can achieve a Q_alpha value of 77.6% and a SOV_alpha value of 73.4%. We briefly describe how our method can be generalized to predicting beta strands and sheets.
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Sood, Gaurav. "Speech Signal Classification Using Support Vector Machines." Thesis, 2009. http://hdl.handle.net/2005/1094.

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Hidden Markov Models (HMMs) are, undoubtedly, the most employed core technique for Automatic Speech Recognition (ASR). Nevertheless, we are still far from achieving high‐performance ASR systems. Some alternative approaches, most of them based on Artificial Neural Networks (ANNs), were proposed during the late eighties and early nineties. Some of them tackled the ASR problem using predictive ANNs, while others proposed hybrid HMM/ANN systems. However, despite some achievements, nowadays, the dependency on Hidden Markov Models is a fact. During the last decade, however, a new tool appeared in th
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22

Frieslaar, Ibraheem. "Robust South African sign language gesture recognition using hand motion and shape." 2014. http://hdl.handle.net/11394/3526.

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Magister Scientiae - MSc<br>Research has shown that five fundamental parameters are required to recognize any sign language gesture: hand shape, hand motion, hand location, hand orientation and facial expressions. The South African Sign Language (SASL) research group at the University of the Western Cape (UWC) has created several systems to recognize sign language gestures using single parameters. These systems are, however, limited to a vocabulary size of 20 – 23 signs, beyond which the recognition accuracy is expected to decrease. The first aim of this research is to investigate the use of t
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Rashwan, Abdullah. "Automatic Driver Fatigue Monitoring Using Hidden Markov Models and Bayesian Networks." Thesis, 2013. http://hdl.handle.net/10012/8082.

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The automotive industry is growing bigger each year. The central concern for any automotive company is driver and passenger safety. Many automotive companies have developed driver assistance systems, to help the driver and to ensure driver safety. These systems include adaptive cruise control, lane departure warning, lane change assistance, collision avoidance, night vision, automatic parking, traffic sign recognition, and driver fatigue detection. In this thesis, we aim to build a driver fatigue detection system that advances the research in this area. Using vision in detecting driver fati
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