Traffic Sign Detection and Recognition using Deep Learning

In this video, we build a complete Traffic Sign Detection and Recognition system using Deep Learning from data preparation to model training and real-time testing. You’ll understand how modern computer vision identifies traffic signs on the road and classifies them accurately using CNN-based networks.

What you’ll learn:

✅ Difference between Detection vs Recognition
✅ Dataset preparation, labeling, and augmentation
✅ Deep Learning pipeline: Preprocessing → Training → Evaluation
✅ Model choices (CNN / Transfer Learning) and why they work
✅ Performance metrics: Accuracy, Confusion Matrix, Precision/Recall, mAP (for detection)
✅ Real-time inference workflow (webcam/video) and optimization tips

Applications:

🚗 ADAS (Driver Assistance) • Smart Vehicles • Road Safety Analytics • Autonomous Systems • Smart Cities

⚠️ Note: This project is for learning and research. Always validate thoroughly before any real-world safety deployment.

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#DeepLearning #ComputerVision #TrafficSignRecognition #ObjectDetection #CNN #YOLO #TensorFlow #PyTorch #AI #ADAS

Видео Traffic Sign Detection and Recognition using Deep Learning канала Jack Sparrow Publishers