Decision Forests for Computer Vision and Medical Image Analysis (2013) (Advances in Computer Vision and Pattern Recognition)
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- Synopsis
- This practical and easy-to-follow text explores the theoretical underpinnings of decision forests, organizing the vast existing literature on the field within a new, general-purpose forest model. Topics and features: with a foreword by Prof. Y. Amit and Prof. D. Geman, recounting their participation in the development of decision forests; introduces a flexible decision forest model, capable of addressing a large and diverse set of image and video analysis tasks; investigates both the theoretical foundations and the practical implementation of decision forests; discusses the use of decision forests for such tasks as classification, regression, density estimation, manifold learning, active learning and semi-supervised classification; includes exercises and experiments throughout the text, with solutions, slides, demo videos and other supplementary material provided at an associated website; provides a free, user-friendly software library, enabling the reader to experiment with forests in a hands-on manner.
- Copyright:
- 2013
Book Details
- Book Quality:
- Publisher Quality
- ISBN-13:
- 9781447149293
- Related ISBNs:
- 9781447149286
- 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:
- Antonio Criminisi
- Edited by:
- J Shotton