DocumentCode
295767
Title
Adaptive classification of hand movement
Author
Holden, Eun- Jung ; Roy, Geoffrey G. ; Owens, Robyn
Author_Institution
Dept. of Comput. Sci., Western Australia Univ., Nedlands, WA, Australia
Volume
3
fYear
1995
fDate
Nov/Dec 1995
Firstpage
1373
Abstract
The hand sign classification system classifies hand movement data into Australian Sign Language (AUSLAN) signs. It is built as a fuzzy expert system with an adaptive engine that trains the system to handle variations in the movement data, or to adapt to differences amongst signers. Adaptive fuzzy systems are often compared with neural networks in their adaptability, but unlike neural networks, expert knowledge can be imposed onto the system in the form of rules
Keywords
adaptive systems; expert systems; fuzzy systems; handicapped aids; pattern classification; AUSLAN; Australian Sign Language signs; adaptive classification; adaptive fuzzy system; fuzzy expert system; hand sign classification system; knowledge representation; Adaptive systems; Fingers; Fuzzy systems; Handicapped aids; Hybrid intelligent systems; Image recognition; Kinematics; Neural networks; Shape; Virtual reality;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 1995. Proceedings., IEEE International Conference on
Conference_Location
Perth, WA
Print_ISBN
0-7803-2768-3
Type
conf
DOI
10.1109/ICNN.1995.487358
Filename
487358
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