摘要: 采用边缘检测算子对手写体数字进行特征提取,分别得到数字的水平、垂直、左右对角线方向特征以及全局特征,然后利用Kirsch5个改进的神经网络分类器分别对这种特征进行训练和初分类,最后再利用一个神经网络对个子网络的识别结果进行集成识别,取得BP5BP5了较好的实验效果。
关键词:
BP算法,
Kirsch算子,
手写体数字识别,
神经网络
Abstract: In this paper, five features for handwritten digits based on Kirsch algorithm are extracted, and five neural networks with BP learning algorithm are used to train the five features respectively. A BP neural network is finally used to integrate the outputs of the five sub-networks together. Experiments show that the proposed approach is promising. ;;;
中图分类号:
罗晓斌,董守斌,金连文,徐浩. 集成型神经网络手写体数字识别[J]. , 2002, 28(08): 77-.
LUO Xiaobin1,DONG Shoubing1,JIN Lianwen2,XU Hao3. Handwritten Digit Recognition of An Integrated Neural Network[J]. , 2002, 28(08): 77-.