Takagi–Sugeno–Kang Fuzzy Systems for High-Dimensional Multilabel Classification-Reference-Cited by-同舟云学术

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Takagi–Sugeno–Kang Fuzzy Systems for High-Dimensional Multilabel Classification

Published:2024-06 Issue:6 Volume:32 Page:3790-3804
ISSN:1063-6706
Container-title:IEEE Transactions on Fuzzy Systems
language:
Short-container-title:IEEE Trans. Fuzzy Syst.

Author:

Bian Ziwei¹^ORCID,Chang Qin¹^ORCID,Wang Jian¹^ORCID,Pedrycz Witold²^ORCID,Pal Nikhil R.³^ORCID

Affiliation:

1. College of Science, China University of Petroleum (East China), Qingdao, China

2. Department of Electrical and Computer Engineering, University of Alberta, Edmonton, AB, Canada

3. Electronics and Communication Sciences Unit, Indian Statistical Institute, Calcutta, India

Funder

National Natural Science Foundation of China

National Key Research and Development Program of China

Fundamental Research Funds for the Central Universities

China-CEEC Higher Education Institutions Consortium Program

Introduction Plan for High Talent Foreign Experts

The Belt and Road Innovative Talents Exchange Foreign Experts Project

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/91/10547166/10485465.pdf?arnumber=10485465

Reference59 articles.

1. Feature ranking for enhancing boosting-based multi-label text categorization

2. Multi-label Text Classification with Deep Neural Networks

3. Multi-label text classification based on the label correlation mixture model

4. Multilabel Image Classification With Regional Latent Semantic Dependencies

5. SVM based multi-label learning with missing labels for image annotation

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