Building effective deep neural network architectures one feature at a time

18 May 2017Martin MundtTobias WeisKishore KondaVisvanathan Ramesh

Successful training of convolutional neural networks is often associated with sufficiently deep architectures composed of high amounts of features. These networks typically rely on a variety of regularization and pruning techniques to converge to less redundant states... (read more)

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