DocumentCode
3057054
Title
A connectionist network for simultaneous perception of multiple categories
Author
Basak, Jayanta ; Murthy, C.A. ; Chaudhury, Santanu ; Majumder, D. Dutta
Author_Institution
Nodal Centre for Knowledge Based Computing, ECSU, Calcutta, India
fYear
1992
fDate
30 Aug-3 Sep 1992
Firstpage
37
Lastpage
40
Abstract
A connectionist network is presented for simultaneous perception of multiple categories. These categories provide an adequate explanation of the input features originating from multiple classes. The network optimises an appropriately defined error function for making the inference. A supervised learning algorithm is presented for learning the association between the features and each individual category
Keywords
inference mechanisms; learning systems; neural nets; connectionist network; error function; inference; input features; learning systems; multiple categories; neural nets; simultaneous perception; supervised learning algorithm; Diseases; Humans; Medical diagnosis; Negative feedback; Neural networks; Output feedback; Pattern classification; Problem-solving; Supervised learning; Uncertainty;
fLanguage
English
Publisher
ieee
Conference_Titel
Pattern Recognition, 1992. Vol.II. Conference B: Pattern Recognition Methodology and Systems, Proceedings., 11th IAPR International Conference on
Conference_Location
The Hague
Print_ISBN
0-8186-2915-0
Type
conf
DOI
10.1109/ICPR.1992.201717
Filename
201717
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