Decision Forests for Computer Vision and Medical Image Analysis (Advances in Computer Vision and Pattern Recognition)

Decision Forests for Computer Vision and Medical Image Analysis (Advances in Computer Vision and Pattern Recognition)

by Antonio Criminisi (Editor), Antonio Criminisi (Editor), J Shotton (Editor)

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.

$207.91

Quantity

20+ in stock

More Information

Format: Illustrated
Pages: 392
Edition: 2013
Publisher: Springer
Published: 07 Feb 2013

ISBN 10: 1447149289
ISBN 13: 9781447149286