Ablation study results.

<div><p>Accurately and rapidly detecting objects and their locations in drone-captured images from maritime search and rescue scenarios provides valuable information for rescue operations. The YOLO series, known for its balance between lightweight architecture and high accuracy, has beco...

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Bibliographic Details
Main Author:	Beigeng Zhao (21637197) (author)
Other Authors:	Jiawen Zhao (6580982) (author), Rui Song (331963) (author), Lizhi Yu (12476136) (author), Xia Zhang (41398) (author), Jiren Liu (12901496) (author)
Published:	2025
Subjects:	Biochemistry Space Science Biological Sciences not elsewhere classified Information Systems not elsewhere classified rarely occurring objects rapidly detecting objects propose targeted optimizations modifications significantly improve extra detection head experimental evaluations conducted demonstrated significant progress aware upsampling algorithm proposed model achieves lightweight complexity range div >< p based maritime search enhance yolo11 ’ relative accuracy improvement model ’ maritime search yolo series specific task rescue tasks rescue operations recent advancements method renowned mambayolo across lightweight configurations lightweight architecture include integrating high accuracy heavyweight configurations enhanced yolo11 detect small depth module common challenges code supporting captured images art methods
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Ablation study results.

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