The Research and Application of Image Recognition Based on Improved BP Algorithm

G. Wei, Liu Piyan, Zhao Hai, Mei Zhan
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引用次数: 4

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 recogntion, and we used it to simulate the image recognition in this field of pattern recognition application . The results of the expriments 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.
基于改进BP算法的图像识别研究与应用
神经网络具有自学习和自适应能力,并且具有较强的容错性和鲁棒性,因此在模式识别中有着广泛的应用。本文在图像识别中采用了一种改进的BP算法——柔性BP算法(Flexible BP algorithm, RPROP),并用它来模拟图像识别在模式识别领域的应用。实验结果表明,该方法能较好地克服使用BP算法训练网络可能陷入局部极小值的缺点,在收敛精度和识别速度上有较好的提高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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