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
Link To Document :
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