DocumentCode :
2849615
Title :
Approach to Partially Connected Neural Evolutionary Model with Its Application to Image Recognition
Author :
Shi, Minghui ; Pan, Wei ; De Garis, Hugo ; Chen, Keying
Author_Institution :
Cognitive Sci. Dept., Xiamen Univ., Xiamen, China
fYear :
2009
fDate :
11-13 Dec. 2009
Firstpage :
1
Lastpage :
4
Abstract :
To explore the method for the building of artificial brain, by combing neural network and genetic algorithm, Parcone model (partially connected neural evolutionary model) was proposed and represented, especially for its partially connected structure and evolution algorithm. Comparing with fully connected model, Parcone model can substantially decrease computing amount, while remain strong classification capability. A series of image recognition experiments (including arrow detection, face detection, and facial sex detection) showed the recognition power and effectiveness of the Parcone model. Since the Parcon model had great potential power, it might be expected to improve it to become the basis for the construction of China´s first artificial brain.
Keywords :
artificial organs; brain; face recognition; genetic algorithms; image classification; medical image processing; neural nets; neurophysiology; object detection; Parcone model; arrow detection; artificial brain; classification capability; face detection; facial sex detection; genetic algorithm; image recognition; neural network; partially connected neural evolutionary model; Artificial intelligence; Artificial neural networks; Biological neural networks; Brain modeling; Competitive intelligence; Face detection; Image recognition; Machine intelligence; Neurons; Principal component analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Intelligence and Software Engineering, 2009. CiSE 2009. International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-4507-3
Electronic_ISBN :
978-1-4244-4507-3
Type :
conf
DOI :
10.1109/CISE.2009.5365299
Filename :
5365299
Link To Document :
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