Efficient YOLOv11 with a FasterNet Backbone and Attention for Multi-Class Underwater Object Detection in Nearshore Waters

Underwater multi-class object detection in nearshore waters is essential for intelligent cleaning operations and ecological monitoring. However, strong reflection and scattering interference, color attenuation, frequent occlusion, and non-rigid deformation often cause fine-grained information loss a...

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Detalhes bibliográficos

Principais autores:	Yinghao He, Wenjie Yin, Ruomiao Song, Siyi Zhou, Shimin Shan, Shuo Liu
Formato:	Artigo
Idioma:	Inglês
Publicado em:	MDPI AG 2026-04-01
coleção:	Journal of Marine Science and Engineering
Assuntos:	nearshore underwater detection multi-class object detection YOLOv11 improvement attention mechanism occlusion-aware detection
Acesso em linha:	https://www.mdpi.com/2077-1312/14/9/827
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