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A piecewise-linear simplicial coupling cell for CNN gray-levelimage processing

机译:CNN灰度图像处理的分段线性简单耦合单元

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In this paper, we propose a universal piecewise-linear (PWL) CNN coupling cell, the simplicial cell, which is intended to work with binary as well as gray-level inputs. The construction of the cell is based on the theory of canonical simplicial PWL representations. As a consequence, the coupling function is endowed with important numerical features, namely: the representation of the characteristic cell function is sparse; the family of coupling functions constitutes a Hilbert space; powerful solution algorithms have been developed for the approximation of nonlinear functions, which is particularly useful when the CNN parameters need to be tuned from examples; the parameters can be extracted from a truth table when the CNN is specified analytically
机译:在本文中,我们提出了一种通用的分段线性(PWL)CNN耦合单元,即简单单元,旨在与二进制以及灰度级输入配合使用。单元的构造基于规范的简单PWL表示理论。结果,耦合函数具有重要的数值特征,即:特征单元函数的表示稀疏;耦合函数族构成一个希尔伯特空间;已经开发出了强大的求解算法来逼近非线性函数,当需要从示例中调整CNN参数时,该算法特别有用;通过解析指定CNN时,可以从真值表中提取参数

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