February 2019
Intermediate to advanced
260 pages
6h 3m
English
Let's see now how Siamese network will learn to detect if two images are the same or not. First, we will fit as we solve both of the images:

And, in the end, we will gain the activation values in the last layer, and store those in memory of course.
Next, the derivation is calculated, and the feedback from that derivation will be back propagated to change the network weights in such a way that if the images are similar, then the difference of the encoded values will be small, while if the images are different, then the back propagation step will change the weights in such a way that will cause the difference of ...
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