Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.14279/30408
Title: | Ship detection using sar images based on yolo at Cyprus’s coast | Authors: | Melillos, George Hadjimitsis, Diofantos G. |
Editors: | Palaniappan, Kannappan Seetharaman, Gunasekaran Harguess, Joshua D. |
Major Field of Science: | Engineering and Technology | Field Category: | Civil Engineering | Keywords: | Cyprus;Ship detection;synthetic aperture radar (SAR) images;You Only Look Once (YOLO) | Issue Date: | 6-Jun-2022 | Source: | Geospatial Informatics XII 2022Virtual, Online, 6 - 12 June 2022 | Volume: | 12099 | Conference: | Proceedings of SPIE - The International Society for Optical Engineering | Abstract: | This paper proposes an automatic ship detection approach in Synthetic Aperture Radar (SAR) Images using YOLO deep learning framework. The You Only Look Once (YOLO) model was initially introduced as the first object detection model that combined bounding box prediction and objects classification into a single end-to-end differentiable network. We train the YOLO model on our dataset in this paper for our detector to learn to detect objects in SAR images such as ships. YOLO test results showed an increase in the accuracy of ship detection at Cyprus's Coast and can be applied in the field of ship detection. | URI: | https://hdl.handle.net/20.500.14279/30408 | ISBN: | 9781510650749 | ISSN: | 0277786X | DOI: | 10.1117/12.2614526 | Rights: | © SPIE Attribution-NonCommercial-NoDerivatives 4.0 International |
Type: | Conference Papers | Affiliation : | Cyprus University of Technology ERATOSTHENES Centre of Excellence |
Appears in Collections: | Δημοσιεύσεις σε συνέδρια /Conference papers or poster or presentation |
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