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What is Convolution and Pooling as Strong Priors about?

Convolution and pooling in Convolutional Neural Networks impose infinitely strong priors by hard-coding assumptions about data structure into the architecture. Convolution focuses on local connectivity, weight sharing, and translation equivariance, while pooling emphasizes invariance to small translations, downsampling, and information selection. These fixed assumptions restrict the model

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udemy6061

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