Decision Forests for Computer Vision and Medical Image Analysis

By Antonio Criminisi

Book Overview

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.

• Format: Hardcover
• Language: English
• ISBN: 1447149289
• ISBN13: 9781447149286
• Release Date: February 2013
• Publisher: Springer
• Length: 368 Pages
• Weight: 1.96 lbs.
• Dimensions: 1.0" x 6.3" x 9.5"