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<p>Sea-surface object detection scheme for USV under foggy environment</p>

Online Publishing @ NISCAIR

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Title Statement <p>Sea-surface object detection scheme for USV under foggy environment</p>
 
Added Entry - Uncontrolled Name Zhang, T
Liu, X
Lib, Y
Zhang, M
 
Uncontrolled Index Term Anti-fog enhancement, Detection accuracy, Sea-surface target, Target detection network
 
Summary, etc. <p style="text-align: justify;">Sea-surface target detection is investigated for the visual image-based autonomous control of an Unmanned Surface Vessel (USV). A traditional way is to dehaze for sea-surface images in the previous target detection algorithms. However, it would cause a problem that the image dehaze performance and detection speed are difficult to be balanced. To solve the above problem, a YOLO (You Only Look Once) based target detection network with good anti-fog ability is proposed for sea-surface target detection. In this proposed method, the target detection network is trained off-line to obtain a good anti-fog ability and the target detection is performed on-line. A hazed sample generation model is built based on atmospheric single scattering inverse model to obtain sufficient samples for the off-line training in the proposed method. And then, the target detection network is trained based on the generated samples to obtain good anti-fog ability according to a new learning strategy. Finally, comparative experimental results demonstrate the effectiveness of the proposed target detection algorithm.</p>
 
Publication, Distribution, Etc. Indian Journal of Geo-Marine Sciences (IJMS)
2022-10-05 16:11:45
 
Electronic Location and Access application/pdf
http://op.niscair.res.in/index.php/IJMS/article/view/66765
 
Data Source Entry Indian Journal of Geo-Marine Sciences (IJMS); ##issue.vol## 50, ##issue.no## 11 (2021)
 
Language Note en