18 citations · 69 across the 9 of their papers we have counts for
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cs.CV2022★ 8 cited
Alleviating the Sample Selection Bias in Few-shot Learning by Removing Projection to the Centroid
Jing Xu, Xu Luo, Xinglin Pan +3
Few-shot learning (FSL) targets at generalization of vision models towards unseen tasks without sufficient annotations. Despite the emergence of a number of few-shot learning metho…
cs.CV2022★ 12 cited
Q-Net: Query-Informed Few-Shot Medical Image Segmentation
Qianqian Shen, Yanan Li, Jiyong Jin +1
Deep learning has achieved tremendous success in computer vision, while medical image segmentation (MIS) remains a challenge, due to the scarcity of data annotations. Meta-learning…
cs.CV2022★ 1 cited
Dual Path Structural Contrastive Embeddings for Learning Novel Objects
Bingbin Li, Elvis Han Cui, Yanan Li +2
Learning novel classes from a very few labeled samples has attracted increasing attention in machine learning areas. Recent research on either meta-learning based or transfer-learn…