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.
Produkteigenschaften
- Artikelnummer: 9781447169628
- Medium: Buch
- ISBN: 978-1-4471-6962-8
- Verlag: Springer
- Erscheinungstermin: 23.08.2016
- Sprache(n): Englisch
- Auflage: Softcover Nachdruck of the original 1. Auflage 2013
- Serie: Advances in Computer Vision and Pattern Recognition
- Produktform: Kartoniert, Paperback
- Gewicht: 5913 g
- Seiten: 368
- Format (B x H x T): 155 x 235 x 22 mm
- Ausgabetyp: Kein, Unbekannt