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Machine Learning Techniques Gait by Mason James (26 results)
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Machine Learning Techniques for Gait Biometric Recognition : Using the Ground Reaction Force
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Machine Learning Techniques for Gait Biometric Recognition : Using the Ground Reaction Force
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Machine Learning Techniques for Gait Biometric Recognition: Using the Ground Reaction Force
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Machine Learning Techniques for Gait Biometric Recognition : Using the Ground Reaction Force
Published by Springer International Publishing, 2016
ISBN 10: 331929086X ISBN 13: 9783319290867
Language: English
£ 33.44
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Machine Learning Techniques for Gait Biometric Recognition : Using the Ground Reaction Force
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Machine Learning Techniques for Gait Biometric Recognition : Using the Ground Reaction Force
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
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Machine Learning Techniques for Gait Biometric Recognition : Using the Ground Reaction Force
Published by Springer International Publishing, Springer International Publishing, 2018
ISBN 10: 3319804863 ISBN 13: 9783319804866
Language: English
£ 47.68
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Add to basketTaschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book focuses on how machine learning techniques can be used to analyze and make use of one particular category of behavioral biometrics known as the gait biometric. A comprehensive Ground Reaction Force (GRF)-based Gait Biometrics Recognition framework is proposed and validated by experiments. In addition, an in-depth analysis of existing recognition techniques that are best suited for performing footstep GRF-based person recognition is also proposed, as well as a comparison of feature extractors, normalizers, and classifiers configurations that were never directly compared with one another in any previous GRF recognition research. Finally, a detailed theoretical overview of many existing machine learning techniques is presented, leading to a proposal of two novel data processing techniques developed specifically for the purpose of gait biometric recognition using GRF.This book introduces novel machine-learning-based temporal normalization techniques bridges research gaps concerning the effect of footwear and stepping speed on footstep GRF-based person recognition provides detailed discussions of key research challenges and open research issues in gait biometrics recognition compares biometrics systems trained and tested with the same footwear against those trained and tested with different footwear.
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Machine Learning Techniques for Gait Biometric Recognition : Using the Ground Reaction Force
Published by Springer International Publishing, 2016
ISBN 10: 331929086X ISBN 13: 9783319290867
Language: English
£ 47.68
Convert currency£ 12.11 shipping from Germany to United KingdomQuantity: 1 available
Add to basketBuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book focuses on how machine learning techniques can be used to analyze and make use of one particular category of behavioral biometrics known as the gait biometric. A comprehensive Ground Reaction Force (GRF)-based Gait Biometrics Recognition framework is proposed and validated by experiments. In addition, an in-depth analysis of existing recognition techniques that are best suited for performing footstep GRF-based person recognition is also proposed, as well as a comparison of feature extractors, normalizers, and classifiers configurations that were never directly compared with one another in any previous GRF recognition research. Finally, a detailed theoretical overview of many existing machine learning techniques is presented, leading to a proposal of two novel data processing techniques developed specifically for the purpose of gait biometric recognition using GRF.This book introduces novel machine-learning-based temporal normalization techniques bridges research gaps concerning the effect of footwear and stepping speed on footstep GRF-based person recognition provides detailed discussions of key research challenges and open research issues in gait biometrics recognition compares biometrics systems trained and tested with the same footwear against those trained and tested with different footwear.
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Hardcover. Condition: Brand New. 260 pages. 9.25x6.25x0.75 inches. In Stock.
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Machine Learning Techniques for Gait Biometric Recognition
Published by Springer International Publishing, Springer International Publishing Mär 2018, 2018
ISBN 10: 3319804863 ISBN 13: 9783319804866
Language: English
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
Seller rating 5 out of 5 stars
£ 47.68
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Add to basketTaschenbuch. Condition: Neu. Neuware -This book focuses on how machine learning techniques can be used to analyze and make use of one particular category of behavioral biometrics known as the gait biometric. A comprehensive Ground Reaction Force (GRF)-based Gait Biometrics Recognition framework is proposed and validated by experiments. In addition, an in-depth analysis of existing recognition techniques that are best suited for performing footstep GRF-based person recognition is also proposed, as well as a comparison of feature extractors, normalizers, and classifiers configurations that were never directly compared with one another in any previous GRF recognition research. Finally, a detailed theoretical overview of many existing machine learning techniques is presented, leading to a proposal of two novel data processing techniques developed specifically for the purpose of gait biometric recognition using GRF.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 260 pp. Englisch.
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Machine Learning Techniques for Gait Biometric Recognition
Published by Springer International Publishing, Springer International Publishing Feb 2016, 2016
ISBN 10: 331929086X ISBN 13: 9783319290867
Language: English
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
Seller rating 5 out of 5 stars
£ 47.68
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Add to basketBuch. Condition: Neu. Neuware -This book focuses on how machine learning techniques can be used to analyze and make use of one particular category of behavioral biometrics known as the gait biometric. A comprehensive Ground Reaction Force (GRF)-based Gait Biometrics Recognition framework is proposed and validated by experiments. In addition, an in-depth analysis of existing recognition techniques that are best suited for performing footstep GRF-based person recognition is also proposed, as well as a comparison of feature extractors, normalizers, and classifiers configurations that were never directly compared with one another in any previous GRF recognition research. Finally, a detailed theoretical overview of many existing machine learning techniques is presented, leading to a proposal of two novel data processing techniques developed specifically for the purpose of gait biometric recognition using GRF.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 260 pp. Englisch.
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Machine Learning Techniques for Gait Biometric Recognition
Published by Springer International Publishing Mrz 2018, 2018
ISBN 10: 3319804863 ISBN 13: 9783319804866
Language: English
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Seller rating 5 out of 5 stars
£ 47.68
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Add to basketTaschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book focuses on how machine learning techniques can be used to analyze and make use of one particular category of behavioral biometrics known as the gait biometric. A comprehensive Ground Reaction Force (GRF)-based Gait Biometrics Recognition framework is proposed and validated by experiments. In addition, an in-depth analysis of existing recognition techniques that are best suited for performing footstep GRF-based person recognition is also proposed, as well as a comparison of feature extractors, normalizers, and classifiers configurations that were never directly compared with one another in any previous GRF recognition research. Finally, a detailed theoretical overview of many existing machine learning techniques is presented, leading to a proposal of two novel data processing techniques developed specifically for the purpose of gait biometric recognition using GRF.This book introduces novel machine-learning-based temporal normalization techniques bridges research gaps concerning the effect of footwear and stepping speed on footstep GRF-based person recognition provides detailed discussions of key research challenges and open research issues in gait biometrics recognition compares biometrics systems trained and tested with the same footwear against those trained and tested with different footwear 260 pp. Englisch.
-
Machine Learning Techniques for Gait Biometric Recognition
Published by Springer International Publishing Feb 2016, 2016
ISBN 10: 331929086X ISBN 13: 9783319290867
Language: English
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Seller rating 5 out of 5 stars
£ 47.68
Convert currency£ 9.52 shipping from Germany to United KingdomQuantity: 2 available
Add to basketBuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book focuses on how machine learning techniques can be used to analyze and make use of one particular category of behavioral biometrics known as the gait biometric. A comprehensive Ground Reaction Force (GRF)-based Gait Biometrics Recognition framework is proposed and validated by experiments. In addition, an in-depth analysis of existing recognition techniques that are best suited for performing footstep GRF-based person recognition is also proposed, as well as a comparison of feature extractors, normalizers, and classifiers configurations that were never directly compared with one another in any previous GRF recognition research. Finally, a detailed theoretical overview of many existing machine learning techniques is presented, leading to a proposal of two novel data processing techniques developed specifically for the purpose of gait biometric recognition using GRF.This book introduces novel machine-learning-based temporal normalization techniques bridges research gaps concerning the effect of footwear and stepping speed on footstep GRF-based person recognition provides detailed discussions of key research challenges and open research issues in gait biometrics recognition compares biometrics systems trained and tested with the same footwear against those trained and tested with different footwear 260 pp. Englisch.
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Machine Learning Techniques for Gait Biometric Recognition
Published by Springer International Publishing, 2018
ISBN 10: 3319804863 ISBN 13: 9783319804866
Language: English
£ 43.12
Convert currency£ 21.63 shipping from Germany to United KingdomQuantity: Over 20 available
Add to basketCondition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Introduces novel machine-learning-based temporal normalization techniquesBridges research gaps concerning the effect of footwear and stepping speed on footstep GRF-based person recognitionProvides detailed discussions of key research challe.
-
Machine Learning Techniques for Gait Biometric Recognition
Published by Springer International Publishing, 2016
ISBN 10: 331929086X ISBN 13: 9783319290867
Language: English
£ 43.12
Convert currency£ 21.63 shipping from Germany to United KingdomQuantity: Over 20 available
Add to basketCondition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Introduces novel machine-learning-based temporal normalization techniquesBridges research gaps concerning the effect of footwear and stepping speed on footstep GRF-based person recognitionProvides detailed discussions of key research challe.
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Condition: New. Print on Demand pp. 223.
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Add to basketCondition: New. PRINT ON DEMAND pp. 223.
