A Ship Detection Method Based on Video Image in Inland Waterway

The construction of smart waterways is the core point to promote the high-quality development of inland waterway transportation, which puts higher requirements on the precise real-time monitoring of moving ships. However, traditional methods, including manual counting and LiDAR monitoring, are limited by accuracy and environmental adaptability, making it difficult to obtain accurate and comprehensive monitoring information of navigation vessels. In contrast, video image processing technology, with advanced algorithms and intelligent models, can comprehensively analyze waterway scenes and achieve real-time and accurate monitoring of waterway traffic. In order to achieve accurate channel flow through ship target detection, we propose an inland waterway ship target detection method based on an improved deep learning model. We also proposed a loss function optimization method suitable for moving ships in inland waterways. By collecting a large amount of ship video data in real waterway scenes, we verified that the proposed method has high detection accuracy.