A Lightweight Block With Information Flow Enhancement for Convolutional Neural Networks-Reference-Cited by-同舟云学术

A Lightweight Block With Information Flow Enhancement for Convolutional Neural Networks

Author:

Bao Zhiqiang¹^ORCID,Yang Shunzhi¹,Huang Zhenhua¹^ORCID,Zhou MengChu²^ORCID,Chen Yunwen³

Affiliation:

1. School of Computer Science, South China Normal University, Guangzhou, China

2. Department of Electrical and Computer Engineering, New Jersey Institute of Technology, Newark, NJ, USA

3. Research and Development Department, DataGrand Inc., Shanghai, China

Funder

National Natural Science Foundation of China

Basic and Applied Basic Research Foundation of Guangdong Province

Ministry of Science and Higher Education of the Russian Federation as part of World-class Research Center Program: Advanced Digital Technologies

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Media Technology

Link

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2. EPSANet: An efficient pyramid squeeze attention block on convolutional neural network;zhang;Proc Asian Conf Comput Vis,2022

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