Aiming at the problem of poor detection effect of MobileNet-SSD algorithm when the target is at the edge of the image or the target is small in human target detection, this paper proposes a human target detection method based on MobileNet- SSD combined with frame difference method. Firstly, the coarse position of the moving target is obtained based on the frame difference method; Secondly, the motion region of the target is calculated based on the rough position, and the region is intercepted in the detection image to achieve the acquisition of the adaptive region of interest (ROI), and then the ROI is sent into the MobileNet-SSD model to achieve human target detection; Finally, using the human target detection method based on MobileNet-SSD combined with frame difference method to carry out the human target detection experiment. The results show that the human target detection method based on MobileNet-SSD combined with frame difference method can effectively detect the human target in the image edge region without affecting the original detection speed.
To reduce the impact of ship swaying motion on the on-board equipment during movement in complex sea conditions, and improve the performance of on-board equipment in the operation of the ship. Based on the theory of seakeeping, the relationship between the sailing state of a ship and its motion performance under specific sea conditions was studied to address the issue of the ship's sailing state (collectively referred to as the heading and speed) during functioning under sailing conditions; And the multi body dynamics simulation software was used to simulate and analyze the nozzle response characteristics and initial disturbance of on-board equipment during function under different sailing states. The research results indicate that adjusting the ship's navigation state during the on-board equipment in the operation can reduce the disturbance caused by ship sway, and provide guiding strategies for optimizing the ship's navigation state during the function of on-board equipment.
Aiming at the problems of personnel intrusion and random placement of goods affecting driving safety in the process of forklift operation, an obstacle target detection and distance detection method for forklift operation based on improved YOLOv5 network is proposed. First, in view of the problem that the target is small and difficult to detect when the distance between people is long, the YOLOv5 network is improved to improve the accuracy of target detection; for the problem of tracking loss caused by the detection target being occluded, the target tracking algorithm and ranging algorithm are introduced to realize the target detection tracking recognition and distance detection. The experimental results show that the detection accuracy of the improved YOLOv5 network is improved by 4%; within the dangerous distance range, the distance detection error is within 5%, which meets the requirements of real-time detection and distance detection and can be used to detect potentially dangerous situations during operation and give an early warning.
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