Yang, Defu and Solihin, Mahmud Iwan and Zhao, Yawen and Yao, Benchun and Chen, Chaoran and Cai, Bingyu and Machmudah, Affiani (2024) A review of intelligent ship marine object detection based on RGB camera. IET Image Processing, 18 (2). pp. 281-297. ISSN 1751-9659
Full text not available from this repository. (Request a copy)Abstract
The article presents a comprehensive summary of Intelligent Ship Marine Object Detec tion (ISMOD) based on the RGB Camera. Marine object detection plays a pivotal role in enabling intelligent ships to acquire crucial data and security assurances for autonomous navigation. Among the various detection sensors, the RGB Camera is an informative and cost-effective tool with a wide range of civil applications. In the beginning, the ISMOD metrics based on the RGB camera is analyzed from three significant aspects, namely accuracy, speed, and robustness. Subsequently, the latest research status and comparative overview are presented, encompassing three mainstream detection methods: traditional detection, deep learning detection, and sensor fusion detection. Finally, the existing challenges of ISMOD are discussed and future development trends are recommended. The results demonstrate that forthcoming development will predominantly concentrate on deep learning approaches, complemented by other techniques. It is imperative to advance detection performance in domains such as deep fusion, multi-feature extraction, multi-fusion technology, and lightweight detection architecture
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | Intelligent Ship; Marine Object Detection; RGB Camera; Review; Computer Vision |
| Subjects: | Navigation, Guidance, & Control |
| Depositing User: | Mrs Titi Herawati |
| Date Deposited: | 08 Dec 2025 03:40 |
| Last Modified: | 08 Dec 2025 03:40 |
| URI: | https://karya.brin.go.id/id/eprint/55780 |


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