DocumentCode :
2649478
Title :
Rotation invariant neocognitron
Author :
Ting, Christopher Hian-Ann
Author_Institution :
Defence Sci. Organ., Singapore
fYear :
1991
fDate :
18-21 Nov 1991
Firstpage :
2216
Abstract :
A biologically inspired method that would reduce the computation load of the neocognitron supervised model is proposed. This method also provides a way to extend the neocognitron´s invariance properties to include rotation invariance. The key idea is to incorporate a magnocellular pathway into Fukushima´a algorithm. A basic shift in the paradigm is that an input is said to be recognized when and only when one of the winners of the magnocellular pathway is validated by the parvocellular pathway. This is a modification of the original model where only the activities of the (parvocellular) grandmother cells indicate recognition. The rotation invariance comes easily by making the magnocellular pathway produce an orientation winner for each grandmother cell, exploiting the Zk-symmetry in the cell-planes of the first stage. Then, with another round of competition, the magnocellular pathway submits a few hypotheses for validification. The author has implemented this method on transputers. The simulation program can recognize numerals in arbitrary orientation
Keywords :
learning systems; neural nets; pattern recognition; Fukushima´a algorithm; learning systems; magnocellular pathway; neural nets; parvocellular pathway; rotation invariant neocognitron; Biological system modeling; Biology computing; Computer architecture; Computer networks; Filters; Fourier transforms; Image recognition; Military computing; Physics computing; Visual system;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 1991. 1991 IEEE International Joint Conference on
Print_ISBN :
0-7803-0227-3
Type :
conf
DOI :
10.1109/IJCNN.1991.170717
Filename :
170717
Link To Document :
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