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A SCALABLE PATTERN RECOGNITION METHOD

机译:可扩展的模式识别方法

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摘要

This paper put forward a scalable pattern recognition system that has knowledge-increasable ability for solving problems of complex or large quantities of classes. Since multiple classifiers work in parallel during the training process and dynamic grouping technique is adopted on recognition, performance on both scalability and recognition rate has improved greatly. Our method can not only accelerate calculation speed and improve recognition rate but also be extended easily and freely. It can be used in pattern recognition such as face, fingerprint and character. The constructive method of the system shows the generality. Experimental results prove its reasonableness and feasibility.
机译:本文提出了一种可扩展的模式识别系统,具有可观的能力,可以解决复杂或大量类别的问题。由于多个分类器在训练过程和动态分组技术期间并行工作,因此在识别上采用动态分组技术,因此可扩展性和识别率的性能大大提高了。我们的方法不仅可以加速计算速度并提高识别率,而且还可以轻松而自由地扩展。它可以用于模式识别,例如面部,指纹和字符。系统的建设性方法显示了一般性。实验结果证明了其合理性和可行性。

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