DocumentCode
2373419
Title
Alopex neural networks for manual alphabet recognition
Author
Hamilton, J. ; Micheli-Tzanakou, E.
Author_Institution
Dept. of Biomed. Eng., Rutgers Univ., Piscataway, NJ, USA
fYear
1994
fDate
1994
Firstpage
1109
Abstract
Alopex and backpropagation were used to train neural networks to recognize signs from the American Manual Alphabet. In many cases, the resulting networks gave comparable performance. The Alopex optimization technique did not converge to low error percentages during training as well as backpropagation did; backpropagation gave poorer performance on networks with a small number of hidden nodes
Keywords
backpropagation; Alopex neural networks; Alopex optimization technique; American Manual Alphabet; American Sign Language; deaf people; error percentages; hidden nodes; manual alphabet recognition; neural networks training; nonvocal person communication; Auditory system; Backpropagation; Biomedical engineering; Deafness; Handicapped aids; Neural networks; Pixel; Shape; Stochastic processes; Testing;
fLanguage
English
Publisher
ieee
Conference_Titel
Engineering in Medicine and Biology Society, 1994. Engineering Advances: New Opportunities for Biomedical Engineers. Proceedings of the 16th Annual International Conference of the IEEE
Conference_Location
Baltimore, MD
Print_ISBN
0-7803-2050-6
Type
conf
DOI
10.1109/IEMBS.1994.415347
Filename
415347
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