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Moon Hwan Kim, Teasuk Yoo, Seok Joon Park and Kyungwon Oh
Autonomous Underwater Vehicles (AUVs) have emerged as pivotal tools for intricate underwater missions, spanning seafloor exploration to meticulous inspection of subsea infrastructures such as pipelines and cables. Although terrestrial obstacle avoidance ...
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Meiyan Zhang, Dongyang Zhao, Cailiang Sheng, Ziqiang Liu and Wenyu Cai
As we all know, target detection and tracking are of great significance for marine exploration and protection. In this paper, we propose one Convolutional-Neural-Network-based target detection method named YOLO-Softer NMS for long-strip target detection ...
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Suleiman Abu Kharmeh, Emad Natsheh, Batoul Sulaiman, Mohammad Abuabiah and Saed Tarapiah
Datasets used for artificial-neural-network and machine-learning applications play a vital role in the research and application of such techniques in solving real-life problems. The construction and availability of large datasets to be used in the off-li...
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Alexandra Nunes and Aníbal Matos
Nowadays, semantic segmentation is used increasingly often in exploration by underwater robots. For example, it is used in autonomous navigation so that the robot can recognise the elements of its environment during the mission to avoid collisions. Other...
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Xinyang Zhao, Shaohua Jin, Gang Bian, Yang Cui, Junsen Wang, Yulin Tang and Chao Jiang
In response to the absence of standardized work practices, work safety measures, efficient work procedures, and suitable line planning methods for exploring seabed topography using autonomous underwater vehicles (AUVs) equipped with side-scan sonar syste...
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