DocumentCode
1908457
Title
Connectionist network for feature extraction and classification of English alphabetic characters
Author
Khobragade, Shyam W. ; Ray, Ajoy K.
Author_Institution
Tata Inst. of Fundamental Res., Pune, India
fYear
1993
fDate
1993
Firstpage
1606
Abstract
An nonadaptive connectionist architecture based feature extractor (CAFE) for English alphabetic patterns is presented. Two different adaptive connectionist networks, i.e., the multi-layer backpropagation network (MBPN) and the counter propagation network (CPN) were implemented for classification of the patterns. Their performance analysis is reported. The system is tolerant to translation and deformation and is observed to classify noisy and distorted patterns correctly
Keywords
backpropagation; character recognition; feature extraction; feedforward neural nets; CAFE; English alphabetic characters; counter propagation network; deformation; distorted patterns; feature extraction; multi-layer backpropagation network; nonadaptive connectionist architecture; performance analysis; translation; Adaptive systems; Counting circuits; Feature extraction; Neural networks; Optical arrays; Optical distortion; Optical noise; Optical sensors; Performance analysis; Sensor arrays;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 1993., IEEE International Conference on
Conference_Location
San Francisco, CA
Print_ISBN
0-7803-0999-5
Type
conf
DOI
10.1109/ICNN.1993.298796
Filename
298796
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