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Decision Forests for Computer Vision and Medical Image Analysis

Decision Forests for Computer Vision and Medical Image Analysis (Hardback)

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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.

Computing & ITComputer scienceArtificial intelligenceComputer visionComputing & ITComputer scienceArtificial intelligenceMachine learningComputing & ITComputer scienceArtificial intelligencePattern recognition Publisher: Springer London Ltd Publication Date: 31/01/2013 ISBN-13: 9781447149286  Details: Type: Hardback Format: Books
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