一种基于部分标记SOM和MLP的混合识别方案

Shujing Lu, Chunyun Xiao, Yue Lu
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引用次数: 3

摘要

本文提出了一种基于部分标注双层SOM和MLP分类器的孟加拉语手写体数字识别混合系统。在Kohonen的SOM中引入部分标注机制来降低识别错误率,并采用双层结构来提高SOM分类器的性能。我们的系统利用了方向和密度特征,并首先应用了部分标记的SOM。如果部分标记的SOM不能识别字符,则将其馈送到多层感知器分类器进行进一步处理。对从真实信封中采集的孟加拉语手写体数字样本进行实验,发现该混合系统的正确率达到了96.7%
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Hybrid Recognition Scheme Based on Partially Labeled SOM and MLP
We propose a hybrid system for Bangla handwritten numeral recognition based on partially labeled two-layer SOM and MLP classifiers. Partially labeled mechanism is introduced to the Kohonen's SOM for reducing recognition error rate, and two-layer structure is applied for improving the performance of the SOM classifier. The directional and density features are utilized in our system, and the partially labeled SOM is applied first. In the case that the character cannot be recognized by the partially labeled SOM, it will be feed to a multi-layer perceptron classifier for further processing. The experiments on the Bangla handwritten numeral samples captured from real envelopes have found that the hybrid system achieves 96.7% correct recognition rate
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