5 citations · 10 across the 9 of their papers we have counts for
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cs.CV2025
Brain-inspired analogical mixture prototypes for few-shot class-incremental learning
Wanyi Li, Wei Wei, Yongkang Luo +1
Few-shot class-incremental learning (FSCIL) poses significant challenges for artificial neural networks due to the need to efficiently learn from limited data while retaining knowl…
cs.CV2023★ 5 cited
Glocal Energy-based Learning for Few-Shot Open-Set Recognition
Haoyu Wang, Guansong Pang, Peng Wang +3
Few-shot open-set recognition (FSOR) is a challenging task of great practical value. It aims to categorize a sample to one of the pre-defined, closed-set classes illustrated by few…