CNNs

CNNs are deep neural networks for which the primarily used input is images. CNNs learn the filters (features) that are hand-engineered in traditional algorithms. This independence from prior knowledge and human effort in feature design is a major advantage. They also reduce the number of parameters to be learned with their shared-weights architecture and possess translation invariance characteristics. In the next subsection, we'll discuss the general architecture of a CNN and how it works.

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