October 2018
Intermediate to advanced
246 pages
6h 26m
English
Content preview from Machine Learning Projects for Mobile Applications
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Rectified linear units
The logic behind keeping a rectified linear units (ReLUs) layer is very simple: it replaces all the negative values with 0. This helps us to make CNN mathematically healthier by avoiding negative values:
Here, in this layer, the size of the image is not altered. We will get the same size output as the input only when the negative values are replaced by 0.
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