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Detecting ships from the satellite images using the YOLO algorithm

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Ship detection from remote sensing imagery is a crucial application for maritime security which includes among others traffic surveillance, protection against illegal fisheries, oil discharge control and sea pollution monitoring. This is typically done through the use of an Automated Identification System (AIS), which uses VHF radio frequencies to wirelessly broadcast the ships location, destination and identity to nearby receiver devices on other ships and land-based systems. AIS are very effective at monitoring ships which are legally required to install a VHF transponder, but fail to detect those which are not, and those which disconnect their transponder. So how do you detect these uncooperative ships? This is where satellite imagery can help. Synthetic Aperture Radar (SAR) imagery uses radio waves to image the Earth’s surface. Unlike optical imagery, the wavelengths which the instruments use are not affected by the time of day or meteorological conditions, enabling imagery to be obtained day or night, with cloudy, or clear skies. Satellites are collecting these images which could be used to make algorithms for ship detection and segmentation.

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