Heterogeneous Prototype Learning From Contaminated Faces Across Domains via Disentangling Latent Factors-Reference-Cited by-同舟云学术

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Heterogeneous Prototype Learning From Contaminated Faces Across Domains via Disentangling Latent Factors

Published:2024 Issue: Volume: Page:1-15
ISSN:2162-237X
Container-title:IEEE Transactions on Neural Networks and Learning Systems
language:
Short-container-title:IEEE Trans. Neural Netw. Learning Syst.

Author:

Pang Meng¹^ORCID,Wang Binghui²^ORCID,Ye Mang³^ORCID,Cheung Yiu-Ming⁴^ORCID,Zhou Yintao¹^ORCID,Huang Wei¹^ORCID,Wen Bihan⁵^ORCID

Affiliation:

1. School of Mathemat-ics and Computer Sciences, Nanchang University, Nanchang, China

2. Department of Computer Science, Illinois Institute of Technology, Chicago, IL, USA

3. School of Computer Science, Wuhan University, Wuhan, China

4. Department of Computer Science, Hong Kong Baptist University, Hong Kong, China

5. School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, Singapore

Funder

National Natural Science Foundation of China

NSFC/Research Grants Council (RGC) Joint Research Scheme

General Research Fund of RGC

RGC Senior Research Fellow Scheme

Natural Science Foundation of Jiangxi Province

High-level and Urgently Needed Overseas Talent Programs of Jiangxi Province

Jiangxi Double Thousand Plan

Ministry of Education, Republic of Singapore, through its Start-Up Grant and Academic Research Fund Tier 1

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/5962385/6104215/10516664.pdf?arnumber=10516664

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