Machine Learning and Image Interpretation
Terry Caelli, Walter F. BischofBooks.org participates in affiliate programs including Bookshop.org and the Amazon Services LLC Associates Program. We may earn a commission from qualifying purchases made through links on this page, at no additional cost to you.
Overview
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
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.
Booknews
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 checks between encoding, feature extractions, and known knowledge structures in a given applications domain. Among the technologies are fuzzy conditional rule generation for learning and recognizing three-dimensional objects from two-dimensional images, the Cite system for understanding scenes and recognizing objects, See++, SOO-PIN for picture interpretation networks, and ABC for a biologically motivated understanding of images. Annotation c. by Book News, Inc., Portland, Or.