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Erosion and dilation as solutions to regularization problem

机译:侵蚀和膨胀作为正则化问题的解决方案

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Abstract: In this paper, we show that gray scale dilation, erosion and consequently hit-miss transform, are solutions to a regularization problem. The theory is an extension to the fact that maximum and minimum operators are Green's functions. These morphological operators are used successfully in a morphological shared-weight neural network designed for automatic target recognition and handwritten digit recognition. !11
机译:摘要:在本文中,我们证明了灰度膨胀,腐蚀以及因此而引起的命中丢失变换是正则化问题的解决方案。该理论是对最大和最小算子是格林函数的事实的扩展。这些形态算子已成功用于为目标自动识别和手写数字识别设计的形态共享权重神经网络。 !11

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