Deep Learning for Ship Classification on Medium Resolution SAR Imagery - Moujahid, Bou, Laouz; Rodolphe, Vadaine; Guillaume, Hajduch; Fablet, Ronan (CCSD, 2023)
International audience This research delves into the classification of maritime vessels, utilizing medium-resolution Synthetic Aperture Radar (SAR) imagery obtained from Sentinel-1, alongside Automatic Identification System (AIS) data streams. The investigation is specifically designed to address a ternary classification challenge involving three distinct ship categories: Tanker, Cargo, and Others. Leveraging a dataset comprising over 80,000 ship images, a Convolutional Neural Network (CNN) ensemble is applied. The results reveal a total classification accuracy of 79%.