An Unsupervised Federated Domain Adaptation Method Based on Knowledge Distillation

IF 10.2 1区计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE IEEE transactions on neural networks and learning systems Pub Date : 2024-12-17 DOI:10.1109/tnnls.2024.3510382

Yunpeng Xiao, Yutong Guo, Haipeng Zhu, Chaolong Jia, Qian Li, Rong Wang, Guoyin Wang

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一种基于知识蒸馏的无监督联邦领域自适应方法

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来源期刊

IEEE transactions on neural networks and learning systems COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-COMPUTER SCIENCE, HARDWARE & ARCHITECTURE

CiteScore

23.80

自引率

9.60%

发文量

2102

审稿时长

3-8 weeks

期刊介绍： The focus of IEEE Transactions on Neural Networks and Learning Systems is to present scholarly articles discussing the theory, design, and applications of neural networks as well as other learning systems. The journal primarily highlights technical and scientific research in this domain.

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