Brain-Inspired Fast-and Slow-Update Prompt Tuning for Few-Shot Class-Incremental Learning

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 : 2024-09-18 DOI:10.1109/tnnls.2024.3454237
Hang Ran, Xingyu Gao, Lusi Li, Weijun Li, Songsong Tian, Gang Wang, Hailong Shi, Xin Ning
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大脑启发的快速和慢速更新提示调谐，用于少数几次类增量学习
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来源期刊
IEEE transactions on neural networks and learning systems
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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