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Hands-On Java Deep Learning for Computer Vision
book

Hands-On Java Deep Learning for Computer Vision

by Klevis Ramo
February 2019
Intermediate to advanced content levelIntermediate to advanced
260 pages
6h 3m
English
Packt Publishing
Content preview from Hands-On Java Deep Learning for Computer Vision

Convolutional sliding window 

In this section, we'll resolve the downsides of using a sliding window by using a convolutional sliding window and gain some intuition behind this technique.

Before we delve into this new method, we need to modify the convolution architecture that we've used so far.

Here is a typical CNN:

We have the input, an red, green, and blue (RGB) image with three channels, and here we'll use a small 32 x 32 image. This is followed by a convolution that leaves the first two dimensions unchanged and increases the number of channels to 64, the max pooling layer divides the first two dimensions by 2, and leaves the number ...

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Publisher Resources

ISBN: 9781789613964Supplemental Content