RIASSUNTO
Maritime surveillance systems are used in a wide range of applications such as fisheries control and port surveillance. These systems can rely on ship classification modules providing high level information on the detected ships using data collected through electro-optical sensors. In this work, we will highlight the difficulties of the ship classification problem, propose an algorithm specifically designed to handle scarcely labeled ships datasets and discuss how to integrate the ship image particularities into generic deep learning frameworks.