GitHub

driver-monitoring-system

Real-time AI Driver Drowsiness Detection using Flask, OpenCV & Dlib with live browser camera monitoring and fatigue alerts. VisionSense is a comprehensive ROS2-based computer vision system designed ...
Hacker

Building a Production-Ready Traffic Violation Detection System with YOLOv8 and DeepSORT

Data engineer working on applied AI, data engineering, and production-grade ML systems with a focus on real-world deployment. Traffic violation detection is often presented as a simple computer vision ...
IEEE

PathPilot:OpenCV Based Lane Detection for Safe Navigation

Abstract: Safe navigation is enabled by lane detection, which is an important component of autonomous vehicles and Advanced Driver-Assistance Systems (ADAS). Existing methods struggle with accuracy ...
Frontiers

An effective approach for real-time drowsy driving prediction using quantized fisher-Gabor features and latent-dynamic conditional random fields

Driver drowsiness or fatigue is among the most important factors that cause traffic accidents; therefore, a monitoring system is necessary to detect the state of a driver drowsiness or fatigue. In ...
IEEE

Lane Detection Using Computer Vision Techniques in ADAS Systems

Abstract: Lane detection is a critical component of Advanced Driver Assistance Systems (ADAS) aimed at improving road safety. This paper introduces a real-time lane detection system using computer ...
Frontiers

Computer vision model based robust lane detection using multiple model adaptive estimation methodology

Lane-keeping systems are a major part of advanced driver assistance systems (ADAS). Existing lane detection algorithms are based on either Computer Vision (CV) models or deep learning techniques which ...