DocumentCode
2641861
Title
Perceptrons for image recognition
Author
Lee, Chung-Nim ; Goh, Seung-Cheol
Author_Institution
Dept. of Math., Pohang Inst. of Sci. & Technol., South Korea
fYear
1991
fDate
18-21 Nov 1991
Firstpage
1735
Abstract
The authors describe perceptrons with two hidden layers for recognizing convexity, connectedness and simple connectedness of a digital image. In fact, the perceptron for connectedness is designed to recognize the connectedness of an arbitrary graph. The perceptrons have been implemented in the C language on a Solbourne 5/600 workstation in a UNIX environment. They have been tested on many input digital images in a 16×16 grid
Keywords
neural nets; pattern recognition; C language; Solbourne 5/600 workstation; UNIX environment; arbitrary graph; connectedness; convexity; digital image; hidden layers; image recognition; neural nets; pattern recognition; perceptrons; Character recognition; Digital images; Feedforward neural networks; Image recognition; Lattices; Mathematics; Neural networks; Neurons; Sensor arrays; Terminology;
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.1991.170677
Filename
170677
Link To Document