Abstract
AbstractChina has a vast territory, numerous inland river systems, with abundant water transport resources. More and more ships are traveling in inland waterways. Therefore, the risk of ship accidents in inland waterways is increasing year by year. This paper mainly studies the research and application of the navigation safety risk evaluation index system in bridge area based on image recognition technology. The convolutional neural network based detection model for inland river ships is proposed. Firstly, several common target detection algorithms are compared and analyzed in this paper, and a single-stage target detection algorithm with the best performance is selected, which is combined with the target detection algorithm according to the navigable environment characteristics of the bridge area. On the basis of ship track prediction, this paper studies the quantification of collision, grounding, hitting reef and collision risk and establishes the ship collision risk evaluation model.KeywordsImage recognition technologyBridge area water areaSecurity risk assessmentConvolutional neural network
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