VEHICLE DETECTION AND CALCULATION IN VIDEOS FROM VIDEO SURVEILLANCE TOOLS USING THE YOLOV8 LIBRARY IN THE PYTHON PROGRAMMING LANGUAGE FOR OBJECT DETECTION
https://doi.org/10.5281/zenodo.15682130
Keywords:
YOLOv8 web applications, API, ultralytics, MixUp, MosaicAbstract
In the world of computer vision, the detection of the YOLOv8 object is really distinguished by its extreme accuracy and speed. It is the latest version of the YOLO series and is known for being able to detect objects in real time. YOLOv8 takes web applications, APIs, and image analysis to the next level with high-level object recognition. In this article, we will look at how yolov8 is used to identify an object.
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Xiao Y., Tian Z., Yu J. et al. A review of object detection based on deep learning. Multimed Tools Appl 79, 23729–23791 (2020). https://doi.org/10.1007/s11042-020- 08976-6
Sampath V., Maurtua I., Aguilar Martín J.J. et al. A survey on generative adversarial networks for imbalance problems in computer vision tasks. J Big Data 8, 27 (2021). https://doi.org/10.1186/s40537-021- 00414-0
Carbonell, Jaime G., Ryszard S. Michalski, and Tom M. Mitchell. "An overview of machine learning." Machine learning (1983): 3-23.
Javlon K., Erali M. STRUCTURE AND PRINCIPLE OF OPERATION OF FULLY CONNECTED NEURAL NETWORKS //International Journal of Contemporary Scientific and Technical Research. – 2023. – С. 136-141.
Mustafoyev E., Abdurasulov A. KONVOLYUTSION NEYRON TARMOQLAR (KNT) QO'LLANILISHI: https://doi. org/10.5281/zenodo. 15316208 // Xalqaro fan tarmoqlari jurnali. – 2025. – T. 1. – №. 5. – S. 48-51.
Muxamadiyev A.Sh., Abdullayev Y.Y. TASVIRDAGI OB’YEKTLARNI ANIQLASH USULLARI // Экономика и социум. 2022. No12-2 (103).
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