切换两个模板的细胞神经网络图像维护

2020 International SoC Design Conference (ISOCC) Pub Date : 2020-10-21 DOI:10.1109/ISOCC50952.2020.9332939

K. Kitamura, Y. Uwate, Y. Nishio

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引用次数: 0

摘要

细胞神经网络(CNN)是Chua和Yang在1998年开发的。CNN的性能取决于被称为模板的参数。通过改变模板，将CNN应用到各种图像处理中。CNN处理后的输出图像为二值图像。因此，在此过程中删除了不需要的对象。在本研究中，我们提出了一种切换两个模板的方法，在某一状态下停止图像处理，在灰度状态下输出。

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Maintaining Images by Cellular Neural Networks with Switching Two Templates

The Cellular Neural Networks (CNN) was developed by Chua and Yang in 1998. The performance of the CNN depends on the parameters which are called the template. The CNN is applied to various image processing by changing the template. The output image processed by CNN is a binary image. Therefore, the unnecessary objects are removed in the process. In this research, we propose a method of switching two templates to stop the image processing in a certain state and output in the grayscale state.

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2020 International SoC Design Conference (ISOCC)

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