Résumé:
Deep Learning, within the field of Artificial Intelligence, has emerged as a prominent field renowned for its capacity to discern complex patterns and features directly from raw data. Our project is centered on exploring techniques for detecting lane lines in self-driving cars, leveraging deep learning methodologies, specifically through the application of FCN (Fully Convolutional Network). We aim to conduct a comparative analysis between deep learning approaches and traditional computer vision methods utilizing OpenCV, shedding light on the strengths and limitations of each approach in the context of lane line detection for autonomous vehicles.
