Machine Learning and Image Interpretation

Terry Caelli

ISBN 10: 030645761X / ISBN 13: 9780306457616

Published by Springer Us Nov 1997, 1997

About this Item

Neuware - In this groundbreaking new volume, computer researchers discuss the development of technologies and specific systems that can interpret data with respect to domain knowledge. Although the chapters each illuminate different aspects of image interpretation, all utilize a common approach - one that asserts such interpretation must involve perceptual learning in terms of automated knowledge acquisition and application, as well as feedback and consistency checks between encoding, feature extraction, and the known knowledge structures in a given application domain. The text is profusely illustrated with numerous figures and tables to reinforce the concepts discussed.

Seller Inventory # 9780306457616

Bibliographic Details

• Title: Machine Learning and Image Interpretation
• Publisher: Springer Us Nov 1997
• Publication Date: 1997
• Language: English
• ISBN 10: 030645761X
• ISBN 13: 9780306457616
• Binding: Buch
• Condition: Neu

About this title

Synopsis

In this groundbreaking new volume, computer researchers discuss the development of technologies and specific systems that can interpret data with respect to domain knowledge. Although the chapters each illuminate different aspects of image interpretation, all utilize a common approach - one that asserts such interpretation must involve perceptual learning in terms of automated knowledge acquisition and application, as well as feedback and consistency checks between encoding, feature extraction, and the known knowledge structures in a given application domain. The text is profusely illustrated with numerous figures and tables to reinforce the concepts discussed.

Synopsis

Describes seven original technologies and specific systems that can interpret image data with respect to domain knowledge. They share the notion that processes that reflect how humans apply world knowledge to image data must involve perceptual learning in terms of automated knowledge acquisitions and application as well as feedback and consistency