Patent · US Active

Hybrid neural network pruning

US12248877B2 · kind B2 · utility

1Cited by
1References
18Claims
0Family size

Assignee

Inventors

Key dates

Filing dateDec 19, 2018
Grant dateMar 11, 2025
Priority date
Expiry dateJun 3, 2042

Classification

  • Technology area (CPC G)Physics
  • CPC primaryG06T2207/30252
  • WIPO fieldComputer technology
  • WIPO sectorElectrical engineering

Abstract

A pruned version of a neural network is generated by determining pruned versions of each a plurality of layers of the network. The pruned version of each layer is determined by sorting a set of channels of the layer based on respective weight values of each channel in the set. A percentage of the set of channels are pruned based on the sorting to form a thinned version of the layer. Accuracy of a thinned version of the neural network is tested, where the thinned version of the neural network includes the thinned version of the layer. The thinned version of the layer is used to generate the pruned version of the layer based on the accuracy of the thinned version of the neural network exceeding a threshold accuracy value. A pruned version of the neural network is generated to include the pruned versions of the plurality of layers.

Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.