Symbolic Visual Learning (Hardcover, New)

Some of the fundamental constraints of automated machine vision have been the inability to automatically adapt parameter settings or utilize previous adaptations in changing environments. Symbolic Visual Learning presents research which adds visual learning capabilities to computer vision systems. Using this state-of-the-art recognition technology, the outcome is different adaptive recognition systems that can measure their own performance, learn from their experience and outperform conventional static designs. Written as a companion volume to Early Visual Learning (edited by S. Nayar and T. Poggio), this book is intended for researchers and students in machine vision and machine learning.

General

Imprint:	Oxford UniversityPress
Country of origin:	United States
Release date:	May 1997
First published:	May 1997
Editors:	Katsushi Ikeuchi (School of Computer Science) • Manuela Velosa (School of Computer Science)
Dimensions:	263 x 185 x 22mm (L x W x T)
Format:	Hardcover
Pages:	364
Edition:	New
ISBN-13:	978-0-19-509870-9
Categories:	Books > Computing & IT > Applications of computing > Artificial intelligence > Computer vision Books > Computing & IT > Applications of computing > Artificial intelligence > Neural networks
LSN:	0-19-509870-6
Barcode:	9780195098709

Is the information for this product incomplete, wrong or inappropriate? Let us know about it.

Does this product have an incorrect or missing image? Send us a new image.

Is this product missing categories? Add more categories.

Review This Product

No reviews yet - be the first to create one!