Research on Two-Way Detection of YOLO V5s+Deep Sort Road Vehicles Based on Attention Mechanism

Abstract

YOLO v5 was born when Joseph Redmon, the father of YOLO, announced his retirement from the field of computer vision, and its structure was further optimized on the basis of YOLO v4. After the sort target tracking algorithm was proposed, the deep sort algorithm added the optimization of apparent features on the basis of the sort algorithm, which enables the model to be more suitable for practical situations and more mature for vehicle detection on traffic roads. Focusing on the new direction of road traffic detection, a single camera is used to detect and track dual-channel vehicles. In the process of experimental exploration, a “double vertical line” algorithm is proposed by introducing the attention mechanism into the YOLO v5 structure and combining with the deep sort target tracking algorithm, which provides a new thinking angle and flow chart for vehicle repeat counting. Finally, the detection results of vehicle identity and traffic flow are obtained through experiments, enabling vehicles to be detected and tracked in real time even on roads with a certain speed. In addition, the calculation law avoids the miscalculation of roads with forks, obtains excellent results on vehicle types and traffic flow, and uses id identity to give car information, which significantly improves the possibility that the model can be applied to practical problems.

Helicopter automatic aiming technology for sea targets based on deep learning

“…The network structure is shown in Figure 2. The convolution kernel is set alternately by 3x3 and 1x1, which is more conducive to the extraction of sea target features 9 . The convolution layer extracts the features and then down-sampling by the pooling layer to remove the unimportant parts of the feature map, and finally outputs the final feature in Figure 3.…”

Prayer Hall Vacancy Detection

“…To address this issue, an effective measure to ensure the safe and optimise use o f the prayer facility, particularly during peak prayer times is compulsory. Such improvements may include capacity limits, proper ventilation, enhanced sanitation protocols, and public awareness o f the importance of healthy behavior in communal spaces [7]- [9]. By doing so, the adverse consequences of overcrowding can be reduced by public health promotions and maintain the solemnness o f these communal prayer spaces.…”

“…Lastly, recent studies have suggested using YOLOv5, a state-of-the-art object detection algorithm, in combination with a robust object tracking algorithm like StrongSORT or DeepSORT, in order to improve the effectiveness of object counting [6] [7]. However, these algorithms may not work as well in more complex cases involving two-way tracking, where the direction of an object's motion is difficult to track, such as in cases where objects are moving in opposite directions, (i.e.…”