DocumentCode
2226175
Title
Structure of neural networks for industrial character reader
Author
Hata, Seiji ; Seino, K. ; Yagisawa, Akira
Author_Institution
Fac. of Educ., Kagawa Univ., Takamatsu, Japan
fYear
1993
fDate
15-19 Nov 1993
Firstpage
1888
Abstract
Neural networks to recognize industrial characters are required to achieve high reading reliability. To achieve this high reliability, a method to control the structure of a neural network´s hidden layer has been introduced. The method defines the feature extraction functions of neurons in the hidden layer, and preliminary teaching is so constructed that it gives the hidden layer neurons defined properties. After the desired property attached to the hidden layer neurons, the ordinary backpropagation procedure refines the structure of the neural network
Keywords
automatic optical inspection; backpropagation; character recognition; character recognition equipment; feature extraction; neural nets; backpropagation; feature extraction functions; high reading reliability; industrial character reader; neural network´s hidden layer; neural networks; preliminary teaching; Assembly systems; Character recognition; Computer network reliability; Computer science; Inspection; Manufacturing; Neural networks; Neurons; Production; Reliability engineering;
fLanguage
English
Publisher
ieee
Conference_Titel
Industrial Electronics, Control, and Instrumentation, 1993. Proceedings of the IECON '93., International Conference on
Conference_Location
Maui, HI
Print_ISBN
0-7803-0891-3
Type
conf
DOI
10.1109/IECON.1993.339362
Filename
339362
Link To Document