Joint Category Compactness and Disturbance Reduction for Cross-Domain Classification-Reference-Cited by-同舟云学术

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Joint Category Compactness and Disturbance Reduction for Cross-Domain Classification

Published:2024 Issue: Volume:73 Page:1-14
ISSN:0018-9456
Container-title:IEEE Transactions on Instrumentation and Measurement
language:
Short-container-title:IEEE Trans. Instrum. Meas.

Author:

Jiang Lin¹^ORCID,Wu Jigang¹^ORCID,Zhao Shuping¹^ORCID,Li Jiaxing²^ORCID,Ma Siyuan¹^ORCID

Affiliation:

1. School of Computer Science and Technology, Guangdong University of Technology, Guangzhou, China

2. Institute of Artificial Intelligence, Guangzhou University, Guangzhou, China

Funder

Natural Science Foundation of China

Guangdong Natural Science Foundation

Basic and Applied Basic Research Foundation of Guangdong Province

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/19/10367905/10445301.pdf?arnumber=10445301

Reference53 articles.

1. Cross-Domain Recognition via Projective Cross-Reconstruction

2. Dynamic Instance Domain Adaptation

3. Semi-Supervised Domain-Adaptive Seizure Prediction via Feature Alignment and Consistency Regularization

4. Double-cohesion learning based multiview and discriminant palmprint recognition

5. Learning Spectrum-Invariance Representation for Cross-Spectral Palmprint Recognition

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