AI RESEARCH
Intelligent Traffic Monitoring with YOLOv11: A Case Study in Real-Time Vehicle Detection
arXiv CS.AI
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ArXi:2604.04080v1 Announce Type: cross Recent advancements in computer vision, driven by artificial intelligence, have significantly enhanced monitoring systems. One notable application is traffic monitoring, which leverages computer vision alongside deep learning-based object detection and counting. We present an offline, real-time traffic monitoring system that couples a pre-trained YOLOv11 detector with BoT-SORT/ByteTrack for multi-object tracking, implemented in PyTorch/OpenCV and wrapped in a Qt-based desktop UI.