Fully Convolutional Network-Based Self-Supervised Learning for Semantic Segmentation-Reference-Cited by-同舟云学术

Fully Convolutional Network-Based Self-Supervised Learning for Semantic Segmentation

Published:2022 Issue: Volume: Page:1-11
ISSN:2162-237X
Container-title:IEEE Transactions on Neural Networks and Learning Systems
language:
Short-container-title:IEEE Trans. Neural Netw. Learning Syst.

Author:

Yang Zhengeng¹^ORCID,Yu Hongshan¹^ORCID,He Yong¹^ORCID,Sun Wei¹^ORCID,Mao Zhi-Hong²^ORCID,Mian Ajmal³^ORCID

Affiliation:

1. National Engineering Laboratory for Robot Visual Perception and Control Technology, College of Electrical and Information Engineering, Hunan University, Changsha 410082, China.

2. Department of Electrical and Computer Engineering and the Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA 15260 USA.

3. Department of Computer Science, The University of Western Australia, Perth, WA 6009, Australia.

Funder

National Natural Science Foundation of China

Project of Science Fund for Distinguished Young Scholars of Hunan Province

Key Research and Development Project of Science and Technology Plan of Hunan Province

China Postdoctoral Science Foundation

Project of Talent Innovation and Sharing Alliance of Quanzhou City

Australian Research Council Future Fellowship Award funded by the Australian Government

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Artificial Intelligence,Computer Networks and Communications,Computer Science Applications,Software

Link

http://xplorestaging.ieee.org/ielx7/5962385/6104215/09772739.pdf?arnumber=9772739

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