Monitoring of Irregularity on Sea Surface from Land-Taken Images
Monitoring of irregularities that will occur on the sea surface is important for environmental safety. In this study, photographs taken from the land were used to determine the irregularities on sea surface. The fact that fixed cameras placed on land and scanning the sea surface were installed in ce...
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| Vydáno v: | IEEE NW Russia Young Researchers in Electrical and Electronic Engineering Conference s. 1417 - 1422 |
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| Hlavní autoři: | , |
| Médium: | Konferenční příspěvek |
| Jazyk: | angličtina |
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IEEE
25.01.2022
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| Témata: | |
| ISSN: | 2376-6565 |
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| Abstract | Monitoring of irregularities that will occur on the sea surface is important for environmental safety. In this study, photographs taken from the land were used to determine the irregularities on sea surface. The fact that fixed cameras placed on land and scanning the sea surface were installed in certain regions and the possibility of installing new ones has been an incentive for this study. In the study, the images created by the mucilage experienced in the Marmara Sea at the beginning of 2021 were used as the irregularity data. The authors developed an original model for this study based on traditional image processing methods. In addition, classification was made with a convolutional neural network-based method and the results were compared. |
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| AbstractList | Monitoring of irregularities that will occur on the sea surface is important for environmental safety. In this study, photographs taken from the land were used to determine the irregularities on sea surface. The fact that fixed cameras placed on land and scanning the sea surface were installed in certain regions and the possibility of installing new ones has been an incentive for this study. In the study, the images created by the mucilage experienced in the Marmara Sea at the beginning of 2021 were used as the irregularity data. The authors developed an original model for this study based on traditional image processing methods. In addition, classification was made with a convolutional neural network-based method and the results were compared. |
| Author | Sanver, Ufuk Yesildirek, Aydin |
| Author_xml | – sequence: 1 givenname: Ufuk surname: Sanver fullname: Sanver, Ufuk email: usanver@ticaret.edu.tr organization: Istanbul Commerce University,Department of Computer Engineering,Istanbul,Turkey – sequence: 2 givenname: Aydin surname: Yesildirek fullname: Yesildirek, Aydin email: aydiny@yildiz.edu.tr organization: Yildiz Technical University,Department of Mecahatronics Engineering,Istanbul,Turkey |
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| Snippet | Monitoring of irregularities that will occur on the sea surface is important for environmental safety. In this study, photographs taken from the land were used... |
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| SubjectTerms | Cameras Convolutional neural networks Image processing irregularity on sea surface Land surface monitoring sea surfaces mucilage Safety Sea surface Surface treatment |
| Title | Monitoring of Irregularity on Sea Surface from Land-Taken Images |
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