RIASSUNTO
Ship classification with spaceborne high resolution synthetic aperture radar (SAR) has wide applications in maritime traffic monitoring, fishing law-enforcement operation, marine security, etc. Deep learning, which has the ability of learning features itself, is successfully used in computer vision and artificial intelligence, and introduced into remote sensing field in recent years. In this study, the Italian COSMO-SkyMed SAR images acquired on Jul. 12–15, 2010 were used for ship classification with convolution neural networks in the Google's TensorFlow environment. The results show that cargo ships could be discriminated from non-cargo ships. Due to variations of radar illumination directions and ship poses, more data are necessary for sub-category classification.