Ship detection using SAR images based on YOLO at Cyprus’s coast

George Melillos; Diofantos G. Hadjimitsis

doi:10.1117/12.2614526

27 May 2022 Ship detection using SAR images based on YOLO at Cyprus’s coast

George Melillos, Diofantos G. Hadjimitsis

Proceedings Volume 12099, Geospatial Informatics XII; 1209903 (2022) https://doi.org/10.1117/12.2614526
Event: SPIE Defense + Commercial Sensing, 2022, Orlando, Florida, United States

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.

Conference Presentation

Citation Download Citation

George Melillos and Diofantos G. Hadjimitsis "Ship detection using SAR images based on YOLO at Cyprus’s coast", Proc. SPIE 12099, Geospatial Informatics XII, 1209903 (27 May 2022); https://doi.org/10.1117/12.2614526

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