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Proceedings of the The International Conference on Engineering & MIS 2015最新文献

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Automatic Pattern Recognition with Wavelet Neural Network 基于小波神经网络的模式自动识别
Pub Date : 2015-09-24 DOI: 10.1145/2832987.2833011
A. Belayadi, L. Ait-Gougam, F. Mekideche-Chafa
Automatic recognition of prototype is very broad field which find more and more application in different areas. It consists to categorize and recognize manuscript, letters, or numbers. Several techniques have been applied to deal with the recognition of prototype. Inspired by the operation of the nervous system, we propose, in this paper, to build up artificial neural network of type Wavelet-Multi-Layer Perceptrons (WMLPs) to deal with recognition of numbers captured using a flatbed scanner. We focus on the use of wavelet transfer function and their importance in neural network approach. In addition, we show during this study the essentials stages to go through in order to be able to deal with recognition of number by WMLPs. The data used to train the WMLPs are 63 in total; nevertheless, the result confirmed the accuracy and the effectiveness of WMLPs in the field of number recognition.
原型自动识别是一个非常广阔的领域,在各个领域都有越来越多的应用。它包括对手稿、字母或数字进行分类和识别。针对原型的识别问题,已经应用了多种技术。受神经系统运作的启发,本文提出建立小波多层感知器(WMLPs)型人工神经网络来处理平板扫描仪捕获的数字识别。重点讨论了小波传递函数的应用及其在神经网络中的重要性。此外,我们在本研究中展示了为了能够处理wmlp对数字的识别而需要经历的基本阶段。用于训练wmlp的数据总数为63个;然而,实验结果证实了wmlp在数字识别领域的准确性和有效性。
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引用次数: 3
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Proceedings of the The International Conference on Engineering & MIS 2015
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