Xception: Deep Learning with Depthwise Separable Convolutions
Published: Jul 1, 2017
Abstract
We present an interpretation of Inception modules in convolutional neural networks as being an intermediate step in-between regular convolution and the depthwise separable convolution operation (a depthwise convolution followed by a pointwise convolution). In this light, a depthwise separable convolution can be understood as an Inception module with a maximally large number of towers. This observation leads us to propose a novel deep...
Paper Details
Title
Xception: Deep Learning with Depthwise Separable Convolutions
Published Date
Jul 1, 2017
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