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Springer - Decision Forests for Computer Vision and Medical Image

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Description

Enhance your understanding of machine learning with Decision Forests for Computer Vision and Medical Image Analysis. This text by Springer provides a practical and easy-to-follow guide to the theoretical foundations of decision forests. By organizing the existing literature into a new, general-purpose forest model, this book serves as a comprehensive resource for researchers and practitioners in the field of AI and machine learning. The content explores a flexible decision forest model designed to handle a diverse range of image and video analysis tasks. Readers can examine both the theoretical basis and the practical implementation steps required for successful application. This book is an essential addition to the Advances in Computer Vision and Pattern Recognition series, offering deep insights into the development and use of decision forests for complex data analysis.

Key Features

Includes a foreword by Prof. Y. Amit and Prof. D. Geman regarding their role in the development of decision forests.

Introduces a flexible decision forest model that can address a large and diverse set of image and video analysis tasks.

https://tosheroon.com/uk/3031419529

Organizes vast existing literature within a new, general-purpose forest model for easier study and application.

Provides a practical approach to understanding decision forests for both computer vision and medical image analysis.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
07 February 2013
Listed Since
16 November 2012

Barcode

No barcode data available

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