Fpc: feature map pruning using channel attention mechanism

Yang Liu; Jianqiang Hu; Xiaobao Zhou; Jiaxin Wu

doi:10.1117/12.2627778

14 March 2022 Fpc: feature map pruning using channel attention mechanism

Yang Liu, Jianqiang Hu, Xiaobao Zhou, Jiaxin Wu

Proceedings Volume 12165, International Conference on Intelligent Traffic Systems and Smart City (ITSSC 2021); 121650Y (2022) https://doi.org/10.1117/12.2627778
Event: 2021 International Conference on Intelligent Traffic Systems and Smart City, 2021, Zhengzhou, China

Abstract

Neural networks have the problems of excessive number of parameters and computation due to data noise and redundant filters, which limits the application of neural networks. A feature map pruning method using channel attention (FPC) is proposed to address the problem of excessive accuracy loss of existing pruning methods. Experiments show that the feature graph pruning method using channel attention has better pruning effect with the same accuracy loss.

Citation Download Citation

Yang Liu, Jianqiang Hu, Xiaobao Zhou, and Jiaxin Wu "Fpc: feature map pruning using channel attention mechanism", Proc. SPIE 12165, International Conference on Intelligent Traffic Systems and Smart City (ITSSC 2021), 121650Y (14 March 2022); https://doi.org/10.1117/12.2627778

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available