Deep Visual Waterline Detection for Inland Marine Unmanned Surface Vehicles
نویسندگان
چکیده
Waterline usually plays as an important visual cue for the autonomous navigation of marine unmanned surface vehicles (USVs) in specific waters. However, complexity inland waterline presents a significant challenge development highly efficient computer vision algorithms tailored detection complicated water environment that USVs face. This paper attempts to find solution guarantee effectiveness with general digital camera patrolling variable To this end, deep-learning-based paradigm USVs, named DeepWL, is proposed, which consists two cooperative deep models (termed WLdetectNet and WLgenerateNet, respectively). They afford continuous image-map estimation from single video stream captured on board. Experimental results demonstrate superiority proposed approach via qualitative quantitative assessment concerned performances. Moreover, due its own generality, has potential be applied tasks other areas such coastal
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ژورنال
عنوان ژورنال: Applied sciences
سال: 2023
ISSN: ['2076-3417']
DOI: https://doi.org/10.3390/app13053164