… an ideal detection base to address limitations. Through the combination of YOLOv8 and
the DeepSort tracking algorithm, we have improved the ability to track pedestrians in dynamic …

… , combined with the DeepSORT tracking algorithm, has found … GhostNet for optimized model
complexity. Traditional deep … a GhostNet module to optimize the YOLOv8 architecture. By …

… Multiple Object Tracking (MOT) accuracy and robustness, this … the YOLOv8 medium model,
optimized with a 0.5 detection … , particularly in detecting pedestrians under varied conditions …

… The accuracy of Yolo v8 with the deep sort algorithm is … YOLO v8 represents the culmination
of years of research and … and optimizations to push the boundaries of object detection …

… This paper focuses on two trackers of this type: DeepSORT … In addition, we explore NVIDIA’s
novel optimization … -s 30.81 %, indicating that YOLOv8-s is better at localizing objects with …

… DeepSORT [19], suggesting it might be a more robust choice for high-motion data. … YOLOv8,
as well as keeping the consistency, we chose to analyze all YOLOv8 models in this project. …

… optimize both the backbone and neck portions of the AppleYOLO and introduce the state-of-the-art
target tracking … OC-SORT is superior to DeepSort, ByteTrack and StrongSORT++ in …

… To optimize computational resources, we choose to represent each detected object's spatial
… At this point, the second person from the left is obstructed by bushes, causing YOLOv8 to fail …

… , inspired from DeepSORT, we decided to use … YOLOv8 was introduced but was still
undergoing active development, had many issues and bugs, and the research paper for YOLOv8 …

… optimized the training of the detection model for different hyperparameters. The multithreading
method was used for optimization and improvement, and the DeepSORT … v7 and YOLO v8 …