#011 CNN Why convolutions ?
Why convolutions ? In this post we will talk about why convolutions or convolutional neural networks work so well in a computer vision. Convolutions are very useful when we include them in our neural networks. There are two main advantages of \(Convolutional \) layers over \(Fully\enspace connected\) layers: parameter sharing and sparsity of connections. We can illustrate an example. Let’s say that we have a \(32\times32\times3\) dimensional image. This actually comes from the example from the previous…
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