Melan-YOLO: a dual-strategy framework with custom architectures for accurate and efficient underwater object detection

Abstract Effective autonomous monitoring of marine litter is vital to reduce marine pollution and protect marine ecosystems. However, current underwater detection systems face significant challenges, primarily due to poor image quality caused by light scattering in turbid waters and the limited comp...

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Hlavní autoři:	Andaç Fındıkçı, Mustafa Yasin Erten, Hüseyin Aydilek
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	Nature Portfolio 2026-05-01
Edice:	Scientific Reports
Témata:	Underwater object detection YOLO Deep learning Marine debris Computational efficiency
On-line přístup:	https://doi.org/10.1038/s41598-026-55023-9
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