Ship target detection technology plays a vital role in civilian maritime traffic monitoring and military maritime security protection, and it is the key to ensuring the safety and order of marine activities. In a complex ocean environment, the background information of optical images is complex. The ship images are missed and wrongly detected due to the change in UAV shooting height, so a CSCGhost target detection algorithm is proposed. Experiments denote that compared with the traditional YOLOv10, the mAP increases by 3.2%, the accuracy increases by 9.1 %, and the recall increases by 3.2%, which has a good detection effect and is especially suitable for offshore operations.
Optimization of Ship Small Target Detection Based on YOLOv10 in Complex Ocean Environment
18.10.2024
1770092 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
DOAJ | 2024
|