… a module which can detect and track the pedestrians and cyclists on … pedestrian and cyclists
are not so important as that for the vehicles. After the detecting module, we borrow the SORT …

… In short, our system uses YOLOv7 Deep Learning Network, which performs better in MOT.
In parallel, the DeepSort algorithm is applied to track each detected obstacle. All stages of the …

… In this section, We first introduce YOLOv5 algorithm for target detection task, next Deep
SORT algorithm for target tracking task, then MTCNN, LPRNet and STNet models for license …

… [28] proposed a joint deep learning framework for pedestrian detection, focusing on …
Finally, the multiple confidence rates of bounding boxes are sorted and filtered, and NMS …

… trajectories could be obtained using target detection (YOLOv5) and 433 multi-objective
tracking algorithms (Deep Sort), and the accuracy of pedestrian detection was higher than 90%. …

… techniques have been proposed to deal with deep learning-based pedestrian detection, it is
still a promising … Keypoint-based object detection [30]–[32] is a sort of methods that generate …

… and Deep SORT are implemented for trespassing detection and … detection includes two
main tasks: detection and tracking. In this research, the YOLOv4 is for detection and Deep SORT …

… pedestrian tracking algorithm built upon the StrongSORT framework. This methodology
amalgamates the strengths of both SORT and the deep … algorithms for pedestrian detection. The …

… Deep-SORT-Yolov5 architecture [30] is used for detection and trajectory tracking (Figure 3).
The Deep-SORT… two key steps, including multiobject detection and trajectory tracking. After …

… pedestrian detection and tracking is a significant research area that aims to detect and track
numerous pedestrians in … to combining deep learning and multi-target tracking for pedestrian …