Comparative performance measures of fuzzy ARTMAP, learned vector quantization, and back propagation for handwritten character recognition

[Proceedings 1992] IJCNN International Joint Conference on Neural Networks Pub Date : 1992-06-07 DOI:10.1109/IJCNN.1992.287090

G. Carpenter, S. Grossberg, K. Iizuka

引用次数: 50

Abstract

The authors compare the performance of fuzzy ARTMAP with that of learned vector quantization and backpropagation on a handwritten character recognition task. Training with fuzzy ARTMAP to a fixed criterion used many fewer epochs. Voting with fuzzy ARTMAP yielded the highest recognition rates.<>

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比较性能指标的模糊ARTMAP，学习矢量量化，和反向传播手写字符识别

作者比较了模糊ARTMAP与学习向量量化和反向传播算法在手写体字符识别中的性能。使用模糊ARTMAP到固定准则的训练使用了更少的epoch。使用模糊ARTMAP投票获得了最高的识别率。

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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来源期刊

[Proceedings 1992] IJCNN International Joint Conference on Neural Networks

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