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Machine Learning Techniques Gait by Mason James (29 results)
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Condition: As New. Unread book in perfect condition.
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Condition: As New. Unread book in perfect condition.
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Machine Learning Techniques for Gait Biometric Recognition: Using the Ground Reaction Force
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
£ 50.80
£ 11.98 shipping
Ships from United Kingdom to U.S.A.Quantity: Over 20 available
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Machine Learning Techniques for Gait Biometric Recognition: Using the Ground Reaction Force
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
£ 50.80
£ 11.98 shipping
Ships from United Kingdom to U.S.A.Quantity: Over 20 available
Add to basketCondition: New. In.
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Condition: New. pp. 223.
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Machine Learning Techniques for Gait Biometric Recognition : Using the Ground Reaction Force
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
Condition: New.
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Machine Learning Techniques for Gait Biometric Recognition : Using the Ground Reaction Force
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
Condition: New.
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Condition: New. pp. 223.
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Machine Learning Techniques for Gait Biometric Recognition : Using the Ground Reaction Force
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
Condition: As New. Unread book in perfect condition.
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Machine Learning Techniques for Gait Biometric Recognition : Using the Ground Reaction Force
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
Condition: As New. Unread book in perfect condition.
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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 : Using the Ground Reaction Force
Language: English
Published by Springer International Publishing, Springer International Publishing, 2018
ISBN 10: 3319804863 ISBN 13: 9783319804866
Taschenbuch. 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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Buch. 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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Taschenbuch. Condition: Neu. Machine Learning Techniques for Gait Biometric Recognition | Using the Ground Reaction Force | James Eric Mason (u. a.) | Taschenbuch | xxxiv | Englisch | 2018 | Springer | EAN 9783319804866 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
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Condition: new. Questo è un articolo print on demand.
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Condition: new. Questo è un articolo print on demand.
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Machine Learning Techniques for Gait Biometric Recognition
Language: English
Published by Springer International Publishing Mrz 2018, 2018
ISBN 10: 3319804863 ISBN 13: 9783319804866
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Seller rating 5 out of 5 stars
Taschenbuch. 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
Language: English
Published by Springer International Publishing Feb 2016, 2016
ISBN 10: 331929086X ISBN 13: 9783319290867
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Seller rating 5 out of 5 stars
Buch. 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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Condition: New. Print on Demand pp. 223.
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Condition: New. PRINT ON DEMAND pp. 223.
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Condition: New. Print on Demand pp. 223.
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Condition: New. PRINT ON DEMAND pp. 223.
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Machine Learning Techniques for Gait Biometric Recognition
Language: English
Published by Springer International Publishing, 2018
ISBN 10: 3319804863 ISBN 13: 9783319804866
Condition: 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
Language: English
Published by Springer International Publishing, 2016
ISBN 10: 331929086X ISBN 13: 9783319290867
Condition: 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
Language: English
Published by Springer, Springer Mär 2018, 2018
ISBN 10: 3319804863 ISBN 13: 9783319804866
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. 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 KG, Sachsenplatz 4-6, 1201 Wien 260 pp. Englisch.
-
Machine Learning Techniques for Gait Biometric Recognition
Language: English
Published by Springer, Springer Feb 2016, 2016
ISBN 10: 331929086X ISBN 13: 9783319290867
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
Seller rating 5 out of 5 stars
Buch. Condition: Neu. This item is printed on demand - Print on Demand Titel. 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.
