Maritime man-overboard search based on MOB-Detector with modulated deformable convolution and bi-directional feature fusion network
IntroductionMaritime transport is vital for global trade and cultural exchange, yet it carries inherent risks, particularly accidents at sea. Drones are increasingly valuable in marine search missions. However, Unmanned Aerial Vehicles (UAV) operating at high altitudes often leave only a small porti...
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Frontiers Media S.A.
2025-06-01
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| Series: | Frontiers in Marine Science |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fmars.2025.1547747/full |
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| author | Guokang Xu Jianchuan Yin Jianchuan Yin Jinfeng Zhang Nini Wang |
| author_facet | Guokang Xu Jianchuan Yin Jianchuan Yin Jinfeng Zhang Nini Wang |
| author_sort | Guokang Xu |
| collection | DOAJ |
| description | IntroductionMaritime transport is vital for global trade and cultural exchange, yet it carries inherent risks, particularly accidents at sea. Drones are increasingly valuable in marine search missions. However, Unmanned Aerial Vehicles (UAV) operating at high altitudes often leave only a small portion of a person overboard visible above the water, posing challenges for traditional detection algorithms.MethodsTo tackle this issue, we present the Man-Overboard Detector (MOB-Detector), an anchor-free detector that enhances the accuracy of man-overboard detection. MOB-Detector utilizes the bi-directional feature fusion network to integrate location and semantic features effectively. Additionally, it employs modulated deformable convolution (MDConv), allowing the model to adapt to various geometric variations of individuals in distress.ResultsExperimental validation shows that the MOB-Detector outperformed its nearest competitor by 8.6% in [Metric 1 AP50] and 5.2% in [Metric 2 APsmall], demonstrating its effectiveness for maritime search tasks. Furthermore, we introduce the ManOverboard Benchmark to evaluate algorithms for detecting small objects in maritime environments.DiscussionIn the discussion, the challenge faced by the MOB-Detector in low-visibility environments is discussed, and two future research directions are proposed: optimizing the detector based on the Transformer architecture and developing targeted data augmentation strategies. |
| format | Article |
| id | doaj-art-19e382098d6b4375baaeff75c71c2f13 |
| institution | Kabale University |
| issn | 2296-7745 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Marine Science |
| spelling | doaj-art-19e382098d6b4375baaeff75c71c2f132025-08-20T03:26:33ZengFrontiers Media S.A.Frontiers in Marine Science2296-77452025-06-011210.3389/fmars.2025.15477471547747Maritime man-overboard search based on MOB-Detector with modulated deformable convolution and bi-directional feature fusion networkGuokang Xu0Jianchuan Yin1Jianchuan Yin2Jinfeng Zhang3Nini Wang4Naval Architecture and Shipping College, Guangdong Ocean University, Zhanjiang, ChinaNaval Architecture and Shipping College, Guangdong Ocean University, Zhanjiang, ChinaGuangdong Provincial Key Laboratory of Intelligent Equipment for South China Sea Marine Ranching, Zhanjiang, ChinaSchool of Navigation, Wuhan University of Technology, Wuhan, ChinaCollege of Mathematics and Computer, Guangdong Ocean University, Zhanjiang, ChinaIntroductionMaritime transport is vital for global trade and cultural exchange, yet it carries inherent risks, particularly accidents at sea. Drones are increasingly valuable in marine search missions. However, Unmanned Aerial Vehicles (UAV) operating at high altitudes often leave only a small portion of a person overboard visible above the water, posing challenges for traditional detection algorithms.MethodsTo tackle this issue, we present the Man-Overboard Detector (MOB-Detector), an anchor-free detector that enhances the accuracy of man-overboard detection. MOB-Detector utilizes the bi-directional feature fusion network to integrate location and semantic features effectively. Additionally, it employs modulated deformable convolution (MDConv), allowing the model to adapt to various geometric variations of individuals in distress.ResultsExperimental validation shows that the MOB-Detector outperformed its nearest competitor by 8.6% in [Metric 1 AP50] and 5.2% in [Metric 2 APsmall], demonstrating its effectiveness for maritime search tasks. Furthermore, we introduce the ManOverboard Benchmark to evaluate algorithms for detecting small objects in maritime environments.DiscussionIn the discussion, the challenge faced by the MOB-Detector in low-visibility environments is discussed, and two future research directions are proposed: optimizing the detector based on the Transformer architecture and developing targeted data augmentation strategies.https://www.frontiersin.org/articles/10.3389/fmars.2025.1547747/fullman-overboardmodulated deformable convolutionbi-directional feature fusion networkanchor-free detectormaritime search and rescuesmall object detection |
| spellingShingle | Guokang Xu Jianchuan Yin Jianchuan Yin Jinfeng Zhang Nini Wang Maritime man-overboard search based on MOB-Detector with modulated deformable convolution and bi-directional feature fusion network Frontiers in Marine Science man-overboard modulated deformable convolution bi-directional feature fusion network anchor-free detector maritime search and rescue small object detection |
| title | Maritime man-overboard search based on MOB-Detector with modulated deformable convolution and bi-directional feature fusion network |
| title_full | Maritime man-overboard search based on MOB-Detector with modulated deformable convolution and bi-directional feature fusion network |
| title_fullStr | Maritime man-overboard search based on MOB-Detector with modulated deformable convolution and bi-directional feature fusion network |
| title_full_unstemmed | Maritime man-overboard search based on MOB-Detector with modulated deformable convolution and bi-directional feature fusion network |
| title_short | Maritime man-overboard search based on MOB-Detector with modulated deformable convolution and bi-directional feature fusion network |
| title_sort | maritime man overboard search based on mob detector with modulated deformable convolution and bi directional feature fusion network |
| topic | man-overboard modulated deformable convolution bi-directional feature fusion network anchor-free detector maritime search and rescue small object detection |
| url | https://www.frontiersin.org/articles/10.3389/fmars.2025.1547747/full |
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