Decision Forests for Computer Vision and Medical Image Analysis Hardback
Edited by Antonio Criminisi, J Shotton
Part of the Advances in Computer Vision and Pattern Recognition series
Hardback
Description
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 ina hands-on manner.
Information
-
Item not Available
- Format:Hardback
- Pages:368 pages, 21 Tables, black and white; XIX, 368 p.
- Publisher:Springer London Ltd
- Publication Date:31/01/2013
- Category:
- ISBN:9781447149286
Information
-
Item not Available
- Format:Hardback
- Pages:368 pages, 21 Tables, black and white; XIX, 368 p.
- Publisher:Springer London Ltd
- Publication Date:31/01/2013
- Category:
- ISBN:9781447149286
