Target closest multimedia fusion 23/7/2024 This phase can efficiently direct the network’s attention to the region with the highest target probability, increasing the target recall rate. The target ROI (Region Of Interest) point cloud and image data are initially fused in the pre-fusion stage. In this paper, we propose a novel multi-modal information fusion method to handle multi-object detection in waterway transportation, which introduces the LiDAR (Light Detection And Ranging) dataset to add spatial information and handle the interference of fog and rain. The current traditional object approaches are hard to handle these problems. However, the surveillance video of waterway transportation is often influenced by fog and rain, which can affect the performance of object detection and reduce the efficiency of management. Precise and efficient detection of ship targets is becoming more and more important, which urgently requires intelligent detection methods to ultimately improves shipping management efficiency. With the rapid development of water transportation, ship safety supervision is facing more severe pressures and challenges.
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