Movatterモバイル変換


[0]ホーム

URL:


Skip to content

Navigation Menu

Sign in
Appearance settings

Search code, repositories, users, issues, pull requests...

Provide feedback

We read every piece of feedback, and take your input very seriously.

Saved searches

Use saved searches to filter your results more quickly

Sign up
Appearance settings

License

NotificationsYou must be signed in to change notification settings

TuSimple/sparse-structure-selection

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

6 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

This code is a re-implementation of the imagenet classification experiments in the paperData-Driven Sparse Structure Selection for Deep Neural Networks (ECCV2018).

Citation

If you use our code in your research or wish to refer to the baseline results, please use the following BibTeX entry.

@article{SSS2018  author =   {Zehao Huang and Naiyan Wang},  title =    {Data-Driven Sparse Structure Selection for Deep Neural Networks},  journal =  {ECCV},  year =     {2018}}

Implementation

This code is implemented by a modifiedMXNet which supportsResNeXt-like augmentation. (This version of MXNet does not support cudnn7)

ImageNet data preparation

Download theImageNet dataset and create pass through rec (followingtornadomeet's repository but using unchange mode)

Run

  • modifyconfig/cfgs.py
  • python train.py

Results on ImageNet-1k

About

No description, website, or topics provided.

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages


[8]ページ先頭

©2009-2025 Movatter.jp