• One example of this when working with digit recognition would be to create a specialized neural network that was designed to mimic the way the eye perceives data.

    这方面的一个例子是,当数字识别系统工作时会创建一个专门的神经网络,用它来模拟眼睛感知数据的方法。

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  • The method of handwritten digit recognition based on written direction is adopted.

    采用了一种基于笔道方向的手写体数字识别的方法。

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  • Validating the effectiveness of support vector machine for handwritten digit recognition.

    验证支持向量机用于手写数字识别的有效性。

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  • The paper proposes a method of off-line handwritten digit recognition based on principal curves.

    该文提出了一种基于主曲线的脱机手写数字识别方法。

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  • The paper proposes a method of off-line handwritten digit recognition based on principal curves.

    主要研究了手写体数字识别的特征提取方法,并提出了一种新的边界特征提取方法。

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  • Nowadays, handwritten digit recognition technique is researched importantly.

    手写数字识别技术是近年来研究的热点。

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  • We try to resolve the dynamic fuzzy multi-dimensional problem on the handwritten digit recognition.

    其次,利用动态模糊理论解决手写数字字符识别中的多维特征和动态模糊性问题。

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  • It describes the implementation of two speech recognisers, for isolated and connected digit recognition.

    描述了单呼数字识别和连呼数字识别两种语音识别器的实现。

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  • In this paper, a handwritten digit recognition system based on integrated neural network is set up. The system was consisted of two parts: Learning part, recognition part.

    本文建立了一个集成型神经网络手写体数字识别系统,系统主要由两部分构成,即:学习部分和识别部分。

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  • To improve the accuracy of handwritten digit recognition, this paper applies support vectormachine to handwritten digit recognition and exploits a software system named SVM-HDR.

    为了提高手写数字识别的精度,本文将支持向量机应用于手写数字识别,开发了SVM-HDR软件系统。

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  • This paper introduces a handwritten digit recognition system based on TMS320VC5402. The work principle is presented and the block diagram of hardware and program flow chart are given .

    介绍了基于TMS320VC5402的手写数字识别系统和该系统的基本原理,给出了它的硬件原理图和软件设计程序框图。

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  • Digit recognition, once again, is a common example of classification learning.

    数字识别再一次成为分类学习的常见样本。

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  • Digit recognition, once again, is a common example of classification learning.

    数字识别再一次成为分类学习的常见样本。

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