Few-Shot Semantic Segmentation for Consumer Electronics: An Inter-Class Relation Mining Approach-Reference-Cited by-同舟云学术

Few-Shot Semantic Segmentation for Consumer Electronics: An Inter-Class Relation Mining Approach

Published:2024-02 Issue:1 Volume:70 Page:3709-3721
ISSN:0098-3063
Container-title:IEEE Transactions on Consumer Electronics
language:
Short-container-title:IEEE Trans. Consumer Electron.

Author:

Huang Huafei¹^ORCID,Yuan Xu¹^ORCID,Yu Shuo²^ORCID,Zhao Wenhong³^ORCID,Alfarraj Osama⁴^ORCID,Tolba Amr⁴^ORCID,Xia Feng⁵^ORCID

Affiliation:

1. School of Software, Dalian University of Technology, Dalian, China

2. School of Computer Science and Technology and the Key Laboratory of Social Computing and Cognitive Intelligence, Ministry of Education, Dalian University of Technology, Dalian, China

3. Ultraprecision Machining Center, Zhejiang University of Technology, Hangzhou, China

4. Computer Science Department, Community College, King Saud University, Riyadh, Saudi Arabia

5. School of Computing Technologies, RMIT University, Melbourne, VIC, Australia

Funder

Researchers Supporting Project, King Saud University, Riyadh, Saudi Arabia

Dalian Major Projects of Basic Research

Bintuan Science and Technology Program

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/30/10510045/10460319.pdf?arnumber=10460319

Reference43 articles.

1. CANet: Class-Agnostic Segmentation Networks With Iterative Refinement and Attentive Few-Shot Learning

2. Anti-aliasing Semantic Reconstruction for Few-Shot Semantic Segmentation

3. Learning What Not to Segment: A New Perspective on Few-Shot Segmentation

4. Multimodal sentiment analysis based on fusion methods: A survey

5. CGNet: A Light-Weight Context Guided Network for Semantic Segmentation