Title :
Recognitron-a neural net model for character recognition
Author :
Zurada, Jacek M. ; Jagiello, Krzysztof
Author_Institution :
Dept. of Electr. Eng., Louisville Univ., KY, USA
Abstract :
A neural network model called a recognitron is described. The recognitron uses a global mechanism for feature detection as compared to another net, called the neocognitron, which applied a local detection mechanism. The net consists of four layers and the output subnet. The Hamming net is used as the output subnet. The results of computer simulation of the recognitron are presented to show its ability for extracting and mapping features from noisy images of handwritten characters
Keywords :
character recognition; neural nets; Hamming net; character recognition; computer simulation; feature detection; feature extraction; feature mapping; global mechanism; handwritten characters; local detection mechanism; neural net model; noisy images; recognitron; Biological neural networks; Character recognition; Computer simulation; Computer vision; Data mining; Feature extraction; Image recognition; Neural networks; Neurons; Pattern recognition;
Conference_Titel :
Neural Networks, 1992. IJCNN., International Joint Conference on
Conference_Location :
Baltimore, MD
Print_ISBN :
0-7803-0559-0
DOI :
10.1109/IJCNN.1992.227102
