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Techniques d'apprentissage automatique pour la reconnaissance biométrique de la démarche : utilisation de la zone au sol-
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- Achat immédiatTechniques d'apprentissage automatique pour la reconnaissance biométrique de la démarche : utilisation de la zone au sol
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Lieu où se trouve l'objet : Fairfield, Ohio, États-Unis
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Estimé entre le ven. 4 oct. et le jeu. 10 oct. à 43230
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Numéro de l'objet eBay :364699155877
Dernière mise à jour le 01 sept. 2024 09:16:52 Paris. Afficher toutes les modificationsAfficher toutes les modifications
Caractéristiques de l'objet
- État
- ISBN-13
- 9783319804866
- Type
- NA
- Publication Name
- NA
- ISBN
- 9783319804866
- Book Title
- Machine Learning Techniques for Gait Biometric Recognition : Using the Ground Reaction Force
- Publisher
- Springer International Publishing A&G
- Item Length
- 9.2 in
- Publication Year
- 2018
- Format
- Trade Paperback
- Language
- English
- Illustrator
- Yes
- Item Height
- 0.6 in
- Genre
- Computers, Technology & Engineering, Science
- Topic
- Signals & Signal Processing, Computer Vision & Pattern Recognition, Physics / General
- Item Weight
- 16 Oz
- Item Width
- 6.1 in
- Number of Pages
- Xxxiv, 223 Pages
À propos de ce produit
Product Identifiers
Publisher
Springer International Publishing A&G
ISBN-10
3319804863
ISBN-13
9783319804866
eBay Product ID (ePID)
21038543946
Product Key Features
Book Title
Machine Learning Techniques for Gait Biometric Recognition : Using the Ground Reaction Force
Number of Pages
Xxxiv, 223 Pages
Language
English
Publication Year
2018
Topic
Signals & Signal Processing, Computer Vision & Pattern Recognition, Physics / General
Illustrator
Yes
Genre
Computers, Technology & Engineering, Science
Format
Trade Paperback
Dimensions
Item Height
0.6 in
Item Weight
16 Oz
Item Length
9.2 in
Item Width
6.1 in
Additional Product Features
Intended Audience
Trade
Number of Volumes
1 vol.
Table Of Content
Introduction.- Background.- Experimental Design and Dataset.- Feature Extraction.-Normalization.- Classification.- Measured Performance.- Experimental Analysis.- Conclusion.
Synopsis
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, Introduction.- Background.- Experimental Design and Dataset.- Feature Extraction.-Normalization.- Classification.- Measured Performance.- Experimental Analysis.- Conclusion., 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
LC Classification Number
TK5102.9
Description de l'objet fournie par le vendeur
Informations sur le vendeur professionnel
Premier Books LLC
David Taylor
26C Trolley Sq
19806-3356 Wilmington, DE
United States
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Évaluations en tant que vendeur (1 032 517)
- l***c (227)- Évaluations laissées par l'acheteur.Dernier moisAchat vérifiéBook came packaged well to avoid damage, in great condition. Not sure if the seller delayed shipping or if usps didn’t update the shipping, which is highly likely. Still received and we are happy with our purchase. I had trouble looking up tracking due to the company they used but seller found usps tracking and sent that over quickly. Sellers communication was excellent. Would buy from again. Item as described.
- t***n (2902)- Évaluations laissées par l'acheteur.Dernier moisAchat vérifiéI don't give negatives; However, description was not correct; No price guide was included in this book.As you will see in book pic shown; title states price guide included, no price guide inside. Communication poor, description, no communication price guide missing from this book. Shipping time was weeks before it was even shipped. Blamed the shipping on warehouse. You own & operate a business; your warehouse is not up to standards you change who you do business with. It's your responsibility.
- -***6 (133)- Évaluations laissées par l'acheteur.6 derniers moisAchat vérifiéItem arrived as described and adequately packaged. Ridiculously long shipping time. Seller posts incorrect tracking number and lists the item as shipped. Contacted seller for correct tracking, received a new tracking number with the warning that the number won’t be “live” until the item is shipped. Will you get your item? Yeah, probably. Count on it being delivered 2-3 weeks longer than expected.
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