Advances in Computer Vision and Pattern Recognition

Similarity-Based Pattern Analysis and Recognition

Editors: Pelillo, Marcello (Ed.)

  • Provides a coherent overview of the emerging field of non-Euclidean similarity learning
  • Presents a broad range of perspectives on similarity-based pattern analysis and recognition methods, from purely theoretical challenges to practical, real-world applications
  • Includes coverage of both supervised and unsupervised learning paradigms, as well as generative and discriminative models
see more benefits

Buy this book

eBook $109.00
price for USA (gross)
  • ISBN 978-1-4471-5628-4
  • Digitally watermarked, DRM-free
  • Included format: PDF, EPUB
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $139.00
price for USA
  • ISBN 978-1-4471-5627-7
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Softcover $139.00
price for USA
  • Customers within the U.S. and Canada please contact Customer Service at 1-800-777-4643, Latin America please contact us at +1-212-460-1500 (Weekdays 8:30am – 5:30pm ET) to place your order.
  • Due: November 4, 2016
  • ISBN 978-1-4471-6950-5
  • Free shipping for individuals worldwide
About this book

This accessible text/reference presents a coherent overview of the emerging field of non-Euclidean similarity learning. The book presents a broad range of perspectives on similarity-based pattern analysis and recognition methods, from purely theoretical challenges to practical, real-world applications. The coverage includes both supervised and unsupervised learning paradigms, as well as generative and discriminative models. Topics and features: explores the origination and causes of non-Euclidean (dis)similarity measures, and how they influence the performance of traditional classification algorithms; reviews similarity measures for non-vectorial data, considering both a “kernel tailoring” approach and a strategy for learning similarities directly from training data; describes various methods for “structure-preserving” embeddings of structured data; formulates classical pattern recognition problems from a purely game-theoretic perspective; examines two large-scale biomedical imaging applications.

Table of contents (10 chapters)

  • Introduction: The SIMBAD Project

    Pelillo, Marcello

    Pages 1-10

  • Non-Euclidean Dissimilarities: Causes, Embedding and Informativeness

    Duin, Robert P. W. (et al.)

    Pages 13-44

  • SIMBAD: Emergence of Pattern Similarity

    Buhmann, Joachim M.

    Pages 45-64

  • On the Combination of Information-Theoretic Kernels with Generative Embeddings

    Aguiar, Pedro M. Q. (et al.)

    Pages 67-83

  • Learning Similarities from Examples Under the Evidence Accumulation Clustering Paradigm

    Fred, Ana L. N. (et al.)

    Pages 85-117

Buy this book

eBook $109.00
price for USA (gross)
  • ISBN 978-1-4471-5628-4
  • Digitally watermarked, DRM-free
  • Included format: PDF, EPUB
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $139.00
price for USA
  • ISBN 978-1-4471-5627-7
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Softcover $139.00
price for USA
  • Customers within the U.S. and Canada please contact Customer Service at 1-800-777-4643, Latin America please contact us at +1-212-460-1500 (Weekdays 8:30am – 5:30pm ET) to place your order.
  • Due: November 4, 2016
  • ISBN 978-1-4471-6950-5
  • Free shipping for individuals worldwide
Loading...

Recommended for you

Loading...

Bibliographic Information

Bibliographic Information
Book Title
Similarity-Based Pattern Analysis and Recognition
Editors
  • Marcello Pelillo
Series Title
Advances in Computer Vision and Pattern Recognition
Copyright
2013
Publisher
Springer-Verlag London
Copyright Holder
Springer-Verlag London
eBook ISBN
978-1-4471-5628-4
DOI
10.1007/978-1-4471-5628-4
Hardcover ISBN
978-1-4471-5627-7
Softcover ISBN
978-1-4471-6950-5
Series ISSN
2191-6586
Edition Number
1
Number of Pages
XIV, 291
Number of Illustrations and Tables
19 b/w illustrations, 46 illustrations in colour
Topics