PRUNING- AND DISTILLATION-BASED CONVOLUTIONAL NEURAL NETWORK COMPRESSION METHOD

摘要

A pruning- and distillation-based convolutional neural network compression method (400), comprising: pruning an original convolutional neural network model to obtain a pruned model (S401); performing fine adjustment on parameters of the pruned model (S403); using the original convolutional neural network model as a teacher network of a distillation algorithm, using the pruned model with the parameters having experienced fine adjustment as a student network of the distillation algorithm, and instructing the student network in training by the teacher network according to the distillation algorithm (S405); and using the student network trained according to the distillation algorithm as a compressed convolutional neural network model (S407). According to the method, by using two conventional network compression methods in combination, a convolutional neural network model is more effectively compressed.