A new kind of shadow detector based on CNN-UBN

Author

Wang, Hai-ming ; Zhao, Jian-ye ; Guo, Shi-de ; Yu, Dao-eieng

Author_Institution

Dept. of Electron., Peking Univ., Beijing, China

Volume

1

fYear

2002

fDate

2002

Firstpage

69

Abstract

In this paper, a new kind of two-dimensional cellular automata (CA) is studied. Several algorithmic rules are discovered that can be used to design new cellular neural networks (CNNs) that can implement a shadow detector for character recognition. The Boolean expressions and learning algorithms are introduced in detail. The results of computer simulation confirm that this new approach is simpler and more effective than that given in the literature. Furthermore, these results also confirm that we can design a new cellular neural network with CA rules and find a novel method to design CNNs.

Keywords

Boolean functions; cellular automata; cellular neural nets; character recognition; learning (artificial intelligence); 2D cellular automata; Boolean functions; cellular neural networks; character recognition; complex valued weight; learning algorithms; shadow detector; universal binary neurons; Algorithm design and analysis; Application software; Cellular neural networks; Computer simulation; Design methodology; Detectors; Equations; Image processing; Integrated circuit interconnections; Parallel processing;

fLanguage

English

Publisher

ieee

Conference_Titel

Machine Learning and Cybernetics, 2002. Proceedings. 2002 International Conference on

Print_ISBN

0-7803-7508-4

Type

conf

DOI

10.1109/ICMLC.2002.1176711

Filename

1176711