DocumentCode :
2534766
Title :
A programmable vision chip for CNN based algorithms
Author :
Dupret, A. ; Klein, J.O. ; Nshare, A.
Author_Institution :
Inst. d´´Electron. Fondamentale, Univ. de Paris-Sud, Orsay, France
fYear :
2000
fDate :
2000
Firstpage :
207
Lastpage :
212
Abstract :
In this paper, an original architecture of cellular neural network (CNN) vision chip is addressed. In the introduction, an analyse of the limitations of the usual approaches leads us to propose an original architecture. The paper is dedicated to the description of the three main blocks of our vision chip. Then, the major building blocks are detailed. Finally, design considerations and the practical implementation of a typical CNN algorithm are discussed
Keywords :
cellular neural nets; computer vision; convolution; mixed analogue-digital integrated circuits; neural net architecture; cellular neural network; convolution; digital analog processor; neural net architecture; programmable vision chip; Algorithm design and analysis; Buildings; Cellular neural networks; Circuits; Computer architecture; Concurrent computing; Image processing; Moore´s Law; Parallel processing; Retina;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Cellular Neural Networks and Their Applications, 2000. (CNNA 2000). Proceedings of the 2000 6th IEEE International Workshop on
Conference_Location :
Catania
Print_ISBN :
0-7803-6344-2
Type :
conf
DOI :
10.1109/CNNA.2000.876846
Filename :
876846
Link To Document :
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