A Chinese military research team has released what it described as the first publicly available visible light-infrared ship detection data set, a resource that could sharpen maritime target recognition for drones, missiles or surveillance systems operating at night or in environments where radar is degraded or suppressed.
The dual-modal ship detection (DMSD) data set contains more than 2,000 paired visible and infrared vessel images and nearly 20,000 annotated instances, according to the peer-reviewed study published in January by the Chinese-language Journal of Radars.
Ship recognition at sea is markedly harder than object detection on land. Maritime environments are shaped by glare, shifting weather, long-range imaging degradation and cluttered backgrounds, all of which can undermine classification accuracy.
The challenge was illustrated in February when an Iranian claim of a successful strike on aircraft carrier USS Abraham Lincoln near the Strait of Hormuz was dismissed by Washington, which said the missiles or drones involved did not come close.
The episode underscored a familiar problem: reaching the vicinity of a ship is one thing, but reliably detecting, identifying and tracking a moving naval target under contested conditions is another.
The study was led by researchers from the Naval Aeronautical University in Yantai, Harbin Engineering University and the Chinese Academy of Sciences’ Institute of Computing Technology.
