Few-Shot Object Detection in Remote Sensing Images via Data Clearing and Stationary Meta-Learning

Nowadays, the focus on few-shot object detection (FSOD) is fueled by limited remote sensing data availability. In view of various challenges posed by remote sensing images (RSIs) and FSOD, we propose a meta-learning-based Balanced Few-Shot Object Detector (B-FSDet), built upon YOLOv9 (GELAN-C versio...

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Detalhes bibliográficos

Principais autores:	Zijiu Yang, Wenbin Guan, Luyang Xiao, Honggang Chen
Formato:	Artigo
Idioma:	Inglês
Publicado em:	MDPI AG 2024-06-01
coleção:	Sensors
Assuntos:	few-shot object detection remote sensing images meta-learning incompletely annotated objects
Acesso em linha:	https://www.mdpi.com/1424-8220/24/12/3882
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