Traffic Sign Recognition with CNN

Traffic Sign Recognition Project Highlights:

Preprocessed and normalized over 43 traffic sign classes using the German Traffic Sign Recognition Benchmark (GTSRB).

Built and trained a CNN model in Python (TensorFlow/Keras).

Integrated data augmentation to boost model generalization.

Results:

Validation Accuracy: 97%

Test Accuracy: 96%

These results demonstrate a robust model capable of classifying diverse traffic signs — a key step toward safer autonomous driving.