A Hybrid Approach to License Plate Recognition: YOLO-v9 and Quantum-Enhanced CNN Model

The integration of quantum machine learning with Convolutional Neural Networks presents a groundbreaking approach to Automatic License Plate Recognition. While traditional CNNs require extensive datasets for high accuracy, this hybrid model leverages quantum computing’s unique capabilities to achieve superior results with limited data. The proposed system combines YOLO v9 for license plate detection with a quantum-optimized CNN for character recognition. The quantum component enhances the model’s pattern recognition and generalization abilities, enabling it to extract more meaningful features from smaller datasets. This quantum advantage results in over 95% accuracy in character recognition, surpassing traditional CNN performance. The hybrid approach not only improves accuracy but also addresses the challenge of limited data availability, paving the way for more efficient and robust AI systems in the quantum era.