Multi-Source and Multi-Target Domain Adaptation Based on Dynamic Generator with Attention-Reference-Cited by-同舟云学术

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Multi-Source and Multi-Target Domain Adaptation Based on Dynamic Generator with Attention

Published:2024 Issue: Volume:26 Page:6891-6905
ISSN:1520-9210
Container-title:IEEE Transactions on Multimedia
language:
Short-container-title:IEEE Trans. Multimedia

Author:

Lu Yuwu¹^ORCID,Huang Haoyu¹^ORCID,Zeng Biqing¹^ORCID,Lai Zhihui²^ORCID,Li Xuelong³^ORCID

Affiliation:

1. School of Software, South China Normal University, Foshan, China

2. College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China

3. School of Artificial Intelligence, Optics and Electronics (iOPEN), Northwestern Polytechnical University, Xi'an, China

Funder

National Natural Science Foundation of China

Basic and Applied Basic Research Foundation of Guangdong Province

Laboratory for Artificial Intelligence in Design

Innovation and Technology Fund, Hong Kong

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6046/10384483/10413589.pdf?arnumber=10413589

Reference60 articles.

1. Anisotropic Graph Convolutional Network for Semi-Supervised Learning

2. Facial Expression Recognition Using Hierarchical Features With Deep Comprehensive Multipatches Aggregation Convolutional Neural Networks

3. Graph Transfer Learning via Adversarial Domain Adaptation with Graph Convolution

4. Unsupervised Multi-Target Domain Adaptation: An Information Theoretic Approach

5. SmsNet: A New Deep Convolutional Neural Network Model for Adversarial Example Detection

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