FILTER SPECIFICITY AS TRAINING CRITERION FOR NEURAL NETWORKS

摘要

A method of training a neural network model includes determining a specificity of multiple filters after a predetermined number of training iterations. The method also includes determining whether to continue training each filter of the multiple filters based at least in part on the specificity. The method further includes classifying an input based on features obtained by convolving the input with the trained filters.