Neural network reduction device, neural network reduction method, and storage medium

Abstract

There is provided a neural network reduction device including: an input section configured to acquire a first neural network including a plurality of processing layers that includes at least one convolutional layer; a generation section configured to generate a third neural network in which at least one second neural network is connected as an additional layer to a stage subsequent to the convolutional layer included in the first neural network; a learning section configured to train the third neural network; a correction section configured to select, as a redundant channel, a channel whose feature value calculated on a basis of a weight parameter of the second neural network establishes a predetermined relationship with a predetermined threshold, delete the redundant channel from the convolutional layer, and correct a weight parameter of the convolutional layer after deletion of the redundant channel on a basis of at least a portion of the weight parameter of the second neural network; a relearning section configured to retrain the third neural network on a basis of correction of the weight parameter of the convolutional layer after the deletion of the redundant channel; and an output section configured to output the retrained third neural network.