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A review of intelligent ship marine object detection based on RGB camera.

Authors :
Yang, Defu
Solihin, Mahmud Iwan
Zhao, Yawen
Yao, Benchun
Chen, Chaoran
Cai, Bingyu
Machmudah, Affiani
Source :
IET Image Processing (Wiley-Blackwell); 2/7/2024, Vol. 18 Issue 2, p281-297, 17p
Publication Year :
2024

Abstract

The article presents a comprehensive summary of Intelligent Ship Marine Object Detection (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. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
17519659
Volume :
18
Issue :
2
Database :
Complementary Index
Journal :
IET Image Processing (Wiley-Blackwell)
Publication Type :
Academic Journal
Accession number :
175229217
Full Text :
https://doi.org/10.1049/ipr2.12959