The Role of Deep Learning-Based Maritime Image Recognition Technology in Ship Collision Avoidance Decision-Making

The goal of this article is to explore the key role of navigation image recognition technology based on deep learning in ship collision avoidance decision-making. By comparing and analyzing the performance of different deep learning algorithms, an optimized image recognition algorithm is proposed to improve the accuracy and real-time performance of ship collision avoidance decision-making. Aiming at the particularity of nautical images, an improved deep learning algorithm is designed and trained and tested on a large number of nautical image data sets. The test results show that the algorithm proposed in this article is superior to the traditional algorithm in recognition accuracy, real-time performance and adaptability to complex scenes. Especially in bad weather and complex sea conditions, the algorithm can still maintain high recognition accuracy and provide reliable information support for ship collision avoidance decision. The navigation image recognition technology based on deep learning proposed in this article effectively improves the efficiency and safety of ship collision avoidance decision. This technology provides a new technical means for the navigation field, and also lays a solid foundation for the future development of the smart ocean.