A Ship Recognition and Load Detection System Based on Deep Learning

As a means of transportation, ships have a significant impact on economic, military, and other fields. Due to the booming development of artificial intelligence technology, intelligent processing in the shipping field is also an inevitable trend. This article introduces the design of a ship recognition and load detection system based on deep learning. Throughout text detection and text recognition technology in natural scenes, it can efficiently detect and recognize ship identification information and water level lines in the marine environment. Combined with the ships information database, it can automatically determine the type and load capacity of ships, thereby improving the efficiency of ships management. The ship waterline detection method proposed in this article combines semantic segmentation technology and attention mechanism and uses Newton Leibniz formula for correction. Even in the presence of complex situations such as wind, waves, water stains, and obstacles, accurate reading of waterlines can be achieved.