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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