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Application of improved BPNN in image restoration-learning coefficient
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作者 Umar Farooq 沈庭芝 +3 位作者 Muhammad Imran 赵三元 Sadia Murawwat 王清云 《Journal of Beijing Institute of Technology》 EI CAS 2012年第4期543-546,共4页
A new method of artificial intelligence based on a new improved back propagation neural network (BPNN) algorithm is partially applied in the problem of image restoration. In order to over- come the inherited issues ... A new method of artificial intelligence based on a new improved back propagation neural network (BPNN) algorithm is partially applied in the problem of image restoration. In order to over- come the inherited issues in conventional back propagation algorithm i.e. slow convergence rate, longer training time, hard to achieve global minima etc. , different methods have been used including the introduction of dynamic learning rate and dynamic momentum coefficient etc. With the passage of time different techniques has been used to improve the dynamicity of these coefficients. The meth- od applied in this paper improves the effect of learning coefficient η by using a new way to modify the value dynamically during learning process. The experimental results show that this helps in im- proving the efficiency overall both in visual effect and quality analysis. 展开更多
关键词 image restoration image processing INTELLIGENT back propagation neural network(BPNN) dynamic learning coefficient
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