DocumentCode
2200461
Title
The Research and Application of Image Recognition Based on Improved BP Algorithm
Author
Wei, Gao ; Piyan, Liu ; Hai, Zhao ; Zhan, Mei
Author_Institution
Inst. of Inf. & Technol., Northeastern Univ., Shenyang, China
fYear
2010
fDate
1-3 Nov. 2010
Firstpage
80
Lastpage
83
Abstract
Neural network has self-learning and adaptive ability, and has strong fault tolerance and robustness, so it has a broad applications in the pattern recognition. In this paper, we adopt an improved BP algorithm-Flexible BP algorithm (RPROP) in the image recognition, and we used it to simulate the image recognition in this field of pattern recognition application . The results of the experiments show that this method can better overcome the shortcoming that use the BP algorithm trained the network, which may fall into the local minimum values, and the method has better improvement in the convergence precision and identification speed.
Keywords
backpropagation; fault tolerance; image recognition; neural nets; fault tolerance; image recognition; improved BP algorithm-flexible BP algorithm; neural network; pattern recognition; BP Neural Network; Image Recognition; RPROP;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Networks and Intelligent Systems (ICINIS), 2010 3rd International Conference on
Conference_Location
Shenyang
Print_ISBN
978-1-4244-8548-2
Electronic_ISBN
978-0-7695-4249-2
Type
conf
DOI
10.1109/ICINIS.2010.144
Filename
5693684
Link To Document