Convolutional operation of sliding windows In the previous post we learned about the sliding windows object detection algorithm using a \(convnet \), but we saw that it was too slow. In this post we will see how to implement that algorithm convolutionaly. Let’s see what that means. To build up the convolutional implementation of sliding windows, let’s first see how we can turn \(Fully \enspace connected \) layers in our neural network into \(Convolutional\) layes.…
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