1 citations · 1 across the 1 of their papers we have counts for
2 papers
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.CV2024★ 1 cited
Meta-Exploiting Frequency Prior for Cross-Domain Few-Shot Learning
Fei Zhou, Peng Wang, Lei Zhang +5
Meta-learning offers a promising avenue for few-shot learning (FSL), enabling models to glean a generalizable feature embedding through episodic training on synthetic FSL tasks in…