Similarity-Based Pattern Analysis and Recognition (2013) (Advances in Computer Vision and Pattern Recognition)
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- Synopsis
- 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.
- Copyright:
- 2013
Book Details
- Book Quality:
- Publisher Quality
- ISBN-13:
- 9781447156284
- Related ISBNs:
- 9781447156277
- Publisher:
- Springer London
- Date of Addition:
- 12/21/20
- Copyrighted By:
- Springer London, London
- Adult content:
- No
- Language:
- English
- Has Image Descriptions:
- No
- Categories:
- Nonfiction, Computers and Internet
- Submitted By:
- Bookshare Staff
- Usage Restrictions:
- This is a copyrighted book.
- Edited by:
- Marcello Pelillo