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Book synopsis

Some of the fundamental constraints of automated machine vision have been the inability automatically to 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.

Book details

Book category Books in English Computing & information technology Computer science Artificial intelligence

• Full title: Symbolic Visual Learning
• Author: Katsushi Ikeuchi, Manuela Velosa, Manuela Veloso
• Language: English
• Binding: Hardback
• Number of pages: 364
• EAN: 9780195098709
• ISBN: 0195098706
• ID: 04863905
• Publisher: Oxford University Press Inc
• Weight: 825 g
• Dimensions: 263 × 185 × 22 mm
• Date of publishing: 29. May 1997

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