Year: 2025
Type: article
Abstract: With the rise of autonomous driving and smart transportation, traffic sign detection is key to road safety and efficient navigation. Traditional methods struggle with lighting, weather, and occlusions, so we propose an Intelligent Traffic Sign Detection System using CNNs for accurate, real-time classification. Trained on the GTSRB dataset with over 50,000 images across 43 categories, our CNN model reduces manual preprocessing and improves accuracy. Data augmentation ensures robustness to real-world conditions. Achieving 92-95% accuracy, the system integrates with autonomous vehicles, providing real-time detection and alerts to enhance road safety and navigation.
Authors: Kottam Vishal Reddy -, Bumpelli Rohith -, Mamindla Rahul Sai -, D Saidulu -
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4409802013