The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Dec. 02, 2025

Filed:

Feb. 11, 2021
Applicant:

GE Precision Healthcare Llc, Milwaukee, WI (US);

Inventors:

Rajesh Kumar Tamada, Bengaluru, IN;

Junpyo Hong, San Ramon, CA (US);

Attila Márk Rádics, Nagykovácsi, HU;

Hans Krupakar, San Ramon, CA (US);

Venkata Ratnam Saripalli, Danville, CA (US);

Dibyajyoti Pati, Dublin, CA (US);

Guarav Kumar, Bokaro Steel, IN;

Assignee:

GE Precision Healthcare LLC, Waukesha, WI (US);

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06N 3/082 (2023.01); G06F 18/2115 (2023.01); G06F 18/214 (2023.01); G06N 3/063 (2023.01); G06N 5/04 (2023.01);
U.S. Cl.
CPC ...
G06N 3/082 (2013.01); G06F 18/2115 (2023.01); G06F 18/214 (2023.01); G06N 3/063 (2013.01); G06N 5/04 (2013.01);
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.


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