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Liqian Wang, Shuzhen Fan, Yunxia Liu, Yongfu Li, Cheng Fei, Junliang Liu, Bohan Liu, Yakui Dong, Zhaojun Liu and Xian Zhao
The ocean connects all continents and is an important space for human activities. Ship detection with electro-optical images has shown great potential due to the abundant imaging spectrum and, hence, strongly supports human activities in the ocean. A sui...
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Fumin Wu, Qianqian Chen, Yuanqiao Wen, Changshi Xiao and Feier Zeng
In the field of automatic detection of ship exhaust behavior, a deep learning-based multi-sensor hierarchical detection method for tracking inland river ship chimneys is proposed to locate the ship exhaust behavior detection area quickly and accurately. ...
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Hongdan Liu, Yan Liu, Bing Li and Zhigang Qi
Ship abnormal behavior detection is an essential part of maritime supervision. It can assist maritime departments to conduct real-time supervision on a certain sea area, avoid ship risks, and improve the efficiency of sea area supervision. Given the prob...
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Zhikai Jiang, Li Su and Yuxin Sun
Accurate ship object detection ensures navigation safety and effective maritime traffic management. Existing ship target detection models often have the problem of missed detection in complex marine environments, and it is hard to achieve high accuracy a...
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Hui Zhou, Peng Chen, Yingqiu Li and Bo Wang
Ship detection in large-scene offshore synthetic aperture radar (SAR) images is crucial in civil and military fields, such as maritime management and wartime reconnaissance. However, the problems of low detection rates, high false alarm rates, and high m...
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Xiaobin Hong, Bin Cui, Weiguo Chen, Yinhui Rao and Yuanming Chen
Aiming at the problem that multi-ship target detection and tracking based on cameras is difficult to meet the accuracy and speed requirements at the same time in some complex scenes, an improved YOLOv4 algorithm is proposed, which simplified the network ...
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Jeong-In Hwang, Sung-Ho Chae, Daeseong Kim and Hyung-Sup Jung
For ship detection, X-band synthetic aperture radar (SAR) imagery provides very useful data, in that ship targets look much brighter than surrounding sea clutter due to the corner-reflection effect. However, there are many phenomena which bring out false...
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Feng Guo, Hongbing Ma, Liangliang Li, Ming Lv and Zhenhong Jia
In the realm of maritime target detection, infrared imaging technology has become the predominant modality. Detecting infrared small ships on the sea surface is crucial for national defense and maritime security. However, the challenge of detecting infra...
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Xuan Zhang, Minglu Zhang, Shilong Jiao, Lingyu Sun and Manhong Li
At present, numerous wall-climbing robots have been developed, and applied in ship manufacturing for weld detection to ensure safe navigation. Limited by rigid mechanical structure and complex detection, mostly existing robots are hardly to complete weld...
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Zhou Fang, Xiaoyong Wang, Liang Zhang and Bo Jiang
Currently, deep learning is extensively utilized for ship target detection; however, achieving accurate and real-time detection of multi-scale targets remains a significant challenge. Considering the diverse scenes, varied scales, and complex backgrounds...
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Yingdong Ye, Rong Zhen, Zheping Shao, Jiacai Pan and Yubing Lin
The intelligent perception ability of the close-range navigation environment is the basis of autonomous decision-making and control of unmanned ships. In order to realize real-time perception of the close-range environment of unmanned ships, an enhanced ...
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Rong Zhen, Yingdong Ye, Xinqiang Chen and Liangkun Xu
Aiming at the problem of high-precision detection of AtoN (Aids to Navigation, AtoN) in the complex inland river environment, in the absence of sufficient AtoN image types to train classifiers, this paper proposes an automatic AtoN detection algorithm Ai...
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Xinqiang Chen, Chenxin Wei, Zhengang Xin, Jiansen Zhao and Jiangfeng Xian
Maritime ship detection plays a crucial role in smart ships and intelligent transportation systems. However, adverse maritime weather conditions, such as rain streak and fog, can significantly impair the performance of visual systems for maritime traffic...
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Muhammad Yasir, Abdoul Jelil Niang, Md Sakaouth Hossain, Qamar Ul Islam, Qian Yang and Yuhang Yin
We aimed to improve the performance of ship detection methods in synthetic aperture radar (SAR) images by utilizing machine learning (ML) and artificial intelligence (AI) techniques. The maritime industry faces challenges in collecting precise data due t...
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Nakhyeon Seong, Jeongseon Kim and Sungsu Lim
This paper presents a novel machine learning-based approach for detecting abnormal ship movements using CCTV videos. Our method utilizes graph-based algorithms to analyze ship trajectories and identify anomalies, with a focus on enhancing maritime safety...
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Yongjiu Zou, Jinqiu Zhang, Taili Du, Xingjia Jiang, Hao Wang, Peng Zhang, Yuewen Zhang and Peiting Sun
According to statistics, about 70% of ship fire accidents occur in the engine room, due to the complex internal structure and various combustible materials. Once a fire occurs, it is difficult to extinguish and significantly impacts the crew?s life and p...
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Langyu Wang, Yan Zhang, Yahong Lin, Shuai Yan, Yuanyuan Xu and Bo Sun
Aiming at the problem of insufficient feature extraction, low precision, and recall in sea surface ship detection, a YOLOv5 algorithm based on lightweight convolution and attention mechanism is proposed. We combine the receptive field enhancement module ...
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Krishna Patel, Chintan Bhatt and Pier Luigi Mazzeo
One of the most critical issues that the marine surveillance system has to address is the accuracy of its ship detection. Since it is responsible for identifying potential pirate threats, it has to be able to perform its duties efficiently. In this paper...
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Byung-Sun Kang and Chang-Hyun Jung
Aqua farms will be the most frequently encountered obstacle when autonomous ships sail along the coastal area of Korea. We used YOLOv5 to create a model that detects aquaculture buoys. The distances between the buoys and the camera were calculated based ...
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Zeyuan Shao, Hongguang Lyu, Yong Yin, Tao Cheng, Xiaowei Gao, Wenjun Zhang, Qianfeng Jing, Yanjie Zhao and Lunping Zhang
Accurate detection of sea-surface objects is vital for the safe navigation of autonomous ships. With the continuous development of artificial intelligence, electro-optical (EO) sensors such as video cameras are used to supplement marine radar to improve ...
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