Empirical Evidence Regarding Few-Shot Learning for Scene Classification in Remote Sensing Images

Empirical Evidence Regarding Few-Shot Learning for Scene Classification in Remote Sensing Images

Few-shot learning (FSL) is a learning paradigm which aims to address the issue of machine/deep learning techniques which traditionally need huge amounts of labelled data to work out. The remote sensing (RS) community has explored this paradigm with numerous published studies to date. Nevertheless, t...

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Bibliographic Details
Main Author:	Valdivino Alexandre de Santiago Júnior
Format:	Article
Language:	English
Published:	MDPI AG 2024-11-01
Series:	Applied Sciences
Subjects:	few-shot learning remote sensing image scene classification deep learning statistical tests
Online Access:	https://www.mdpi.com/2076-3417/14/23/10776
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