DocumentCode :
869806
Title :
Shape understanding: knowledge generation and learning
Author :
Les, Zbigniew ; Les, Magdalena
Author_Institution :
Queen Jadwiga Found., Toorak, Vic., Australia
Volume :
16
Issue :
3
fYear :
2004
fDate :
3/1/2004 12:00:00 AM
Firstpage :
343
Lastpage :
353
Abstract :
A method of knowledge generation as part of a shape-understanding method is presented. The proposed method of knowledge generation consists of: learning the description of new a posteriori classes, learning the concept of visual objects, and generation of the visual representation of "inner" objects. The visual concept, as part of the concept of the visual object, is expressed as a set of symbolic names that refers to possible classes of shape. The visual concept can be used to find the visual similarities between different visual objects, perform visual transformations as part of visual thinking capabilities of a system, and memorize a visual object as a symbolic representation. The knowledge obtained in the process of knowledge generation is integrated with an existing knowledge of a shape understanding system and used in the explanatory process. This system of shape understanding (SUS), that is, the implementation of the shape understanding method, is designed to imitate the visual thinking capabilities of the human visual system. The SUS consists of different types of experts that perform different processing and reasoning tasks and is designed to perform visual diagnosis in medical applications.
Keywords :
computer graphics; data mining; learning (artificial intelligence); object recognition; human visual system; knowledge discovery; knowledge generation; learning; medical applications; posteriori classes; reasoning tasks; shape understanding system; visual diagnosis; visual object representation; visual thinking capabilities; Biomedical equipment; Design methodology; Geometry; Human factors; Mathematics; Medical services; Psychology; Shape; Topology; Visual system;
fLanguage :
English
Journal_Title :
Knowledge and Data Engineering, IEEE Transactions on
Publisher :
ieee
ISSN :
1041-4347
Type :
jour
DOI :
10.1109/TKDE.2003.1262188
Filename :
1262188
Link To Document :
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