Search for dissertations about: "HMMs"
Showing result 16 - 20 of 24 swedish dissertations containing the word HMMs.
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16. Machine-Printed and Handwritten Ethiopic Script Recognition
Abstract : A written language is represented by using machine-printed or handwritten symbols called characters. For automatic recognition of written languages, handwritten script can be captured offline (by a scanner) and online (by electronic digital devices), whereas machine-printed text is captured offline. READ MORE
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17. Hidden Markov Models: Identification, Inverse Filtering and Applications
Abstract : A hidden Markov model (HMM) comprises a state with Markovian dynamics that is hidden in the sense that it can only be observed via a noisy sensor. This thesis considers three themes in relation to HMMs, namely, identification, inverse filtering and applications. READ MORE
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18. Using Markov models and a stochastic Lipschitz condition for genetic analyses
Abstract : A proper understanding of biological processes requires an understanding of genetics and evolutionary mechanisms. The vast amounts of genetical information that can routinely be extracted with modern technology have so far not been accompanied by an equally extended understanding of the corresponding processes. READ MORE
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19. Automatic speaker verification on site and by telephone: methods, applications and assessment
Abstract : Speaker verification is the biometric task of authenticating a claimed identity by means of analyzing a spoken sample of the claimant's voice. The present thesis deals with various topics related to automatic speaker verification (ASV) in the context of its commercial applications, characterized by co-operative users, user-friendly interfaces, and requirements for small amounts of enrollment and test data. READ MORE
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20. A Multi-Dimensional Approach to Human Mobility and Transportation Mode Detection Using GPS Data
Abstract : GPS tracking data is an essential resource for analyzing human travel patterns and evaluating the effects on transportation systems. The primary challenge, however, is to accurately identify the modes of transportation within unlabeled GPS data. These approaches range from simple rule-based systems to advanced machine-learning techniques. READ MORE