Abstract
This project seeks to develop a real-time, Python-based, license plate recognition system leveraging deep learning's efficiency and robustness. Employing custom- trained convolutional neural networks alongside targeted object detection algorithms, the system aims to accurately locate and extract license plate information from images and video streams. Extensive data preprocessing and comprehensive model training optimize performance under varying lighting, angles, and minor occlusions. Integration into a user-friendly application further enhances accessibility and practical utility. This project's contribution lies in its applicability to real-world scenarios like traffic management, law enforcement, and vehicle tracking, demonstrating the power of advanced computer vision and machine learning for practical problem-solving in the automotive domain.
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