Title :
A New Face Detection Method with GA-BP Neural Network
Author :
Huang Chen-rong ; Tang Jia-li ; Liu Yi-jun
Author_Institution :
Sch. of Comput. Eng., Nanjing Inst. of Technol., Nanjing, China
Abstract :
In this paper, the BP neural network improved by the genetic algorithm (GA) is applied to the problem of human face detection. GA is used to optimize the initial weights of the BP neural network to make full use of its global optimization and local accurate searching of the BP algorithm. Matlab Software and its neural network toolbox are used to simulate and compute. The experiment results show that the GA-BP neural network has a good performance for face detection. Furthermore, compared with the conventional BP algorithm, the GA-BP learning algorithm has more rapid convergence and better assessment accuracy of detecting quality.
Keywords :
backpropagation; face recognition; genetic algorithms; learning (artificial intelligence); neural nets; BP neural network; GA-BP learning algorithm; GA-BP neural network; Matlab software; face detection method; genetic algorithm; global optimization; human face detection; Biological cells; Face; Face detection; Face recognition; Genetic algorithms; Humans; Training;
Conference_Titel :
Wireless Communications, Networking and Mobile Computing (WiCOM), 2011 7th International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-6250-6
DOI :
10.1109/wicom.2011.6040617