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Example filters by Krizhevsky et al. [3]. Because these filters were learned using the first convolutional layer of the neural network, the represented features are simple, such as the edge orientation and frequency (learned features become progressively more complex with each additional convolutional layer). Reproduced with permission from Alex Krizhevsky, Advances in NIPS 25; published by Curran Associates, Inc., 2012.
