集成型神经网络手写体数字识别

Handwritten Digit Recognition of An Integrated Neural Network

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。

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. ;;;