🚦 Research Focus
Developed an integrated, modular, real-time traffic monitoring system that combines object detection, vehicle analytics, and anomaly detection using deep learning. The system performs automatic licence plate recognition alongside GAN-based anomaly detection for highway surveillance.
Research Details
Real-Time Highway Traffic Analysis and Generative Adversarial Network Based Anomaly Detection and Automatic Licence Plate Recognition
Real-Time Traffic Analysis
Modular pipeline for object detection, vehicle counting, speed estimation, and traffic flow analytics on highway footage.
GAN-Based Anomaly Detection
Generative Adversarial Networks for detecting unusual events and anomalies in surveillance video streams.
Licence Plate Recognition
Automatic ALPR system for real-time vehicle identification from highway camera feeds.
YOLO-based Detection
State-of-the-art YOLO architecture for real-time multi-class object detection at highway speeds.
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