Can you give me a high level overview over how Convolutions work in Neural Networks? I know about Sobel filters and understand how they work, but I don't know how/whether the idea translates to Convolutions. I know a fair bit of Linear Algebra and also understand fully connected layers and activation functions, if that is relevant for the explanation.
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