2021
DOI: 10.48550/arxiv.2112.07282
|View full text |Cite
Preprint
|
Sign up to set email alerts
|

SNF: Filter Pruning via Searching the Proper Number of Filters

Abstract: Convolutional Neural Network (CNN) has an amount of parameter redundancy, filter pruning aims to remove the redundant filters and provides the possibility for the application of CNN on terminal devices. However, previous works pay more attention to designing evaluation criteria of filter importance and then prune less important filters with a fixed pruning rate or a fixed number to reduce convolutional neural networks' redundancy. It does not consider how many filters to reserve for each layer is the most reas… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

0
0
0

Publication Types

Select...

Relationship

0
0

Authors

Journals

citations
Cited by 0 publications
references
References 37 publications
0
0
0
Order By: Relevance

No citations

Set email alert for when this publication receives citations?