Sea-surface object detection scheme for USV under foggy environment
NOPR - NISCAIR Online Periodicals Repository
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Title |
Sea-surface object detection scheme for USV under foggy environment
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Creator |
Zhang, T
Liu, X Li, Y Zhang, M |
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Subject |
Anti-fog enhancement
Detection accuracy Sea-surface target Target detection network |
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Description |
960-968
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 antifog 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. |
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Date |
2022-03-14T09:54:55Z
2022-03-14T09:54:55Z 2021-11 |
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Type |
Article
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Identifier |
2582-6727 (Online); 2582-6506 (Print)
http://nopr.niscair.res.in/handle/123456789/59321 |
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Language |
en
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Publisher |
NIScPR-CSIR, India
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Source |
IJMS Vol.50(11) [November 2021]
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