Python Deep Learning - Second Edition

Xception and MobileNets

The last inception network we'll discuss is Xception (from Extreme Inception). To understand its hypothesis, let's recall that in Chapter 3, Deep Learning Fundamentals, Computer Vision, and Convolutional Layers, we introduced standard and depthwise convolutions. An output slice in standard convolution receives input from all input slices using a single filter. The filter tries to learn features in a 3D space, where two of the dimensions are spatial (the height and width of the slice) and the third is the channel. Therefore, the filter maps both spatial and cross-channel correlations.

All inception blocks so far have started with a dimensionality-reduction 1 x 1 convolution. From our new point of view, this connection ...