DocumentCode :
3466989
Title :
An efficient and compact integration of CMOS image sensors and cellular neural network (CNN) for intelligent processing
Author :
Wu, Chung-Yu ; Yen, Wen-Cheng
Author_Institution :
Dept. of Electron. Eng., Nat. Chiao Tung Univ., Hsinchu, Taiwan
fYear :
1999
fDate :
1999
Firstpage :
232
Lastpage :
236
Abstract :
By using the neuron-bipolar junction transistor (BJT) as phototransistor and single-transistor neuron, the cellular neural network (CNN) can be compactly integrated with CMOS image sensors so that the optical images can be input to the CNN directly for neural image processing. With the neuron-BJT, realized by the parasitic pnp BJT in n-well CMOS technology, the optical-input CNN with symmetric templates can be implemented in very small chip area. The cell area can be as small as 20 μm×24 μm. The simulation results have confirmed the correct function of the proposed optical-input compact CNN
Keywords :
CMOS image sensors; cellular neural nets; image processing; optical neural nets; phototransistors; 20 micron; 24 micron; CMOS image sensors; cellular neural network; neural image processing; neuron-bipolar junction transistor; phototransistor; single-transistor neuron; CMOS image sensors; CMOS technology; Cellular neural networks; Image processing; Integrated optics; Neurons; Optical computing; Optical fiber networks; Optical sensors; Phototransistors;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Multisensor Fusion and Integration for Intelligent Systems, 1999. MFI '99. Proceedings. 1999 IEEE/SICE/RSJ International Conference on
Conference_Location :
Taipei
Print_ISBN :
0-7803-5801-5
Type :
conf
DOI :
10.1109/MFI.1999.815995
Filename :
815995
Link To Document :
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