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Machine Learning Techniques for Gait Biometric Recognition: Using the Ground Rea

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Price:
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ApproximatelyRM 312.26
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eBay item number:364699155877
Last updated on May 19, 2024 21:41:11 MYTView all revisionsView all revisions

Item specifics

Condition
Brand New: A new, unread, unused book in perfect condition with no missing or damaged pages. See all condition definitionsopens in a new window or tab
ISBN-13
9783319804866
Type
NA
Publication Name
NA
ISBN
9783319804866
Book Title
Machine Learning Techniques for Gait Biometric Recognition : Using the Ground Reaction Force
Item Length
9.2 in
Publisher
Springer International Publishing A&G
Publication Year
2018
Format
Trade Paperback
Language
English
Illustrator
Yes
Item Height
0.6 in
Author
James Eric Mason, Issa Traoré, Isaac Woungang
Genre
Technology & Engineering, Computers, Science
Topic
Signals & Signal Processing, Computer Vision & Pattern Recognition, Physics / General
Item Width
6.1 in
Item Weight
16 Oz
Number of Pages
Xxxiv, 223 Pages

About this product

Product Information

Introduction.- Background.- Experimental Design and Dataset.- Feature Extraction.-Normalization.- Classification.- Measured Performance.- Experimental Analysis.- Conclusion.

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
Author
James Eric Mason, Issa Traoré, Isaac Woungang
Format
Trade Paperback
Language
English
Topic
Signals & Signal Processing, Computer Vision & Pattern Recognition, Physics / General
Publication Year
2018
Illustrator
Yes
Genre
Technology & Engineering, Computers, Science
Number of Pages
Xxxiv, 223 Pages

Dimensions

Item Length
9.2 in
Item Height
0.6 in
Item Width
6.1 in
Item Weight
16 Oz

Additional Product Features

Intended Audience
Trade
Number of Volumes
1 Vol.
Lc Classification Number
Tk5102.9
Table of Content
Introduction.- Background.- Experimental Design and Dataset.- Feature Extraction.-Normalization.- Classification.- Measured Performance.- Experimental Analysis.- Conclusion.
Copyright Date
2016

Item description from the seller

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