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Vehicle Detection with YOLOv9 & DeepSORT by abdulrahim.fazli.04 is a document available to read on EtoBox.

What is Vehicle Detection with YOLOv9 & DeepSORT about?

This research article presents a vehicle detection, tracking, and counting system for urban traffic videos using a combination of YOLOv9 and DeepSORT algorithms. The proposed method effectively addresses challenges such as occlusions and high vehicle density, achieving a mean Average Precision (mAP) of 91.4% and operating at an average speed of 12.9 frames per second. The results indicate that this approach is both accurate and efficient for real-time traffic monitoring applications.

Author

abdulrahim.fazli.04

Language

EN