Few-Shot Learning Based on Double Pooling Squeeze and Excitation Attention

Few-Shot Learning Based on Double Pooling Squeeze and Excitation Attention

Training a generalized reliable model is a great challenge since sufficiently labeled data are unavailable in some open application scenarios. Few-shot learning (FSL) aims to learn new problems with only a few examples that can tackle this problem and attract extensive attention. This paper proposes...

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Bibliographic Details
Main Authors:	Qiuyu Xu, Jie Su, Ying Wang, Jing Zhang, Yixin Zhong
Format:	Article
Language:	English
Published:	MDPI AG 2022-12-01
Series:	Electronics
Subjects:	few-shot learning metric learning image classification attention mechanism feature representation
Online Access:	https://www.mdpi.com/2079-9292/12/1/27

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