论文笔记—Flattened convolution neural networks for feedforward acceleration

1. 论文思想

一维滤过器。将三维卷积分解成三个一维卷积。convolution across channels(lateral), vertical and horizontal direction.

论文笔记—Flattened convolution neural networks for feedforward acceleration

2. 计算量对比

论文笔记—Flattened convolution neural networks for feedforward acceleration

变换后计算量:
论文笔记—Flattened convolution neural networks for feedforward acceleration
对比:
论文笔记—Flattened convolution neural networks for feedforward acceleration
论文笔记—Flattened convolution neural networks for feedforward acceleration

3. 总结

因为spatial convolution会带来大量的参数以及是非常耗时的,本文将三维卷积分解成了三个一维的卷积,极大的减少了计算量。其实,本文也引入了不对称卷积,再后来也证实了这种不对称卷积Nx1和1xN,对准确率是有提升的。

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