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

[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

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引用次数: 50

摘要

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

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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[Proceedings 1992] IJCNN International Joint Conference on Neural Networks

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