Support Vector Machines Applications

Editors: Ma, Yunqian, Guo, Guodong (Eds.)

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  • Focus on current developments in the field of Support Vector Machines
  • Illustrates critical applications of support vector machines to important real world problems
  • Provides critical review of the state-of-the-art techniques on SVM, such as domain transfer SVM, object recognition, soft biometrics, and biomedical applications
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eBook $119.00
price for USA in USD
  • ISBN 978-3-319-02300-7
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  • Immediate eBook download after purchase
Hardcover $199.99
price for USA in USD
  • ISBN 978-3-319-02299-4
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Softcover $159.99
price for USA in USD
  • ISBN 978-3-319-34329-7
  • Free shipping for individuals worldwide
  • Institutional customers should get in touch with their account manager
  • Covid-19 shipping restrictions
  • Usually ready to be dispatched within 3 to 5 business days, if in stock
About this book

Support vector machines (SVM) have both a solid mathematical background and practical applications. This book focuses on the recent advances and applications of the SVM, such as image processing, medical practice, computer vision, and pattern recognition, machine learning, applied statistics, and artificial intelligence. The aim of this book is to create a comprehensive source on support vector machine applications.

About the authors

Yunqian Ma is Senior Principal Research Scientist at Honeywell Labs. Guodong Guo is an Assistant Professor at West Virginia University.

Reviews

From the book reviews:

“The book brings substantial contributions to the field of SVMs from both theoretical and practical points of view. The concepts and methods are presented in a clear and accessible way, and the illustrative examples and applications provide a valuable source of inspiration for similar developments. … This book is of considerable value to researchers in the fields of machine learning, data mining, and statistical pattern recognition.” (L. State, Computing Reviews, August, 2014)

Table of contents (8 chapters)

Table of contents (8 chapters)
  • Augmented-SVM for Gradient Observations with Application to Learning Multiple-Attractor Dynamics

    Pages 1-21

    Shukla, Ashwini (et al.)

  • Multi-Class Support Vector Machine

    Pages 23-48

    Wang, Zhe (et al.)

  • Novel Inductive and Transductive Transfer Learning Approaches Based on Support Vector Learning

    Pages 49-103

    Deng, Zhaohong (et al.)

  • Security Evaluation of Support Vector Machines in Adversarial Environments

    Pages 105-153

    Biggio, Battista (et al.)

  • Application of SVMs to the Bag-of-Features Model: A Kernel Perspective

    Pages 155-189

    Wang, Lei (et al.)

Buy this book

eBook $119.00
price for USA in USD
  • ISBN 978-3-319-02300-7
  • Digitally watermarked, DRM-free
  • Included format: EPUB, PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $199.99
price for USA in USD
  • ISBN 978-3-319-02299-4
  • Free shipping for individuals worldwide
  • Institutional customers should get in touch with their account manager
  • Covid-19 shipping restrictions
  • Usually ready to be dispatched within 3 to 5 business days, if in stock
Softcover $159.99
price for USA in USD
  • ISBN 978-3-319-34329-7
  • Free shipping for individuals worldwide
  • Institutional customers should get in touch with their account manager
  • Covid-19 shipping restrictions
  • Usually ready to be dispatched within 3 to 5 business days, if in stock
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Bibliographic Information

Bibliographic Information
Book Title
Support Vector Machines Applications
Editors
  • Yunqian Ma
  • Guodong Guo
Copyright
2014
Publisher
Springer International Publishing
Copyright Holder
Springer International Publishing Switzerland
eBook ISBN
978-3-319-02300-7
DOI
10.1007/978-3-319-02300-7
Hardcover ISBN
978-3-319-02299-4
Softcover ISBN
978-3-319-34329-7
Edition Number
1
Number of Pages
VII, 302
Number of Illustrations
31 b/w illustrations, 56 illustrations in colour
Topics