公开(公告)号：US20220253708A1

公开(公告)日：2022-08-11

申请号：US17174049

申请日：2021-02-11

Applicant: GE Precision Healthcare LLC

Inventor： Rajesh Kumar Tamada ,  Junpyo Hong ,  Attila Márk Rádics ,  Hans Krupakar ,  Venkata Ratnam Saripalli ,  Dibyajyoti Pati ,  Guarav Kumar

IPC: G06N3/08 ,  G06N3/063 ,  G06N5/04 ,  G06K9/62

Abstract: Techniques are provided for compressing deep neural networks using a structured filter pruning method that is extensible and effective. According to an embodiment, a computer-implemented method comprises determining, by a system operatively coupled to a processor, importance scores for filters of layers of a neural network model previously trained until convergence for an inferencing task on a training dataset. The method further comprises removing, by the system, a subset of the filters from one or more layers of the layers based on the importance scores associated with the subset failing to satisfy a threshold importance score value. The method further comprises converting, by the system, the neural network model into a compressed neural network model with the subset of the filters removed.