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@article{167279,
        author = {Dharmaraj Stalin Karunanithi and S.Keerthana and P.Vanitha},
        title = {REAL TIME LANE DETECTION AND TRACKING USING JETSON NANO},
        journal = {International Journal of Innovative Research in Technology},
        year = {2024},
        volume = {11},
        number = {3},
        pages = {740-747},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=167279},
        abstract = {Lane detection is a pivotal technology in the realm of autonomous vehicles, advanced driver assistance systems (ADAS), and traffic monitoring systems. Its ability to perceive and delineate lane markings empowers vehicles to comprehend their position within their surroundings, fostering safer and more efficient navigation. This project delves into the development and implementation of efficient lane detection system, meticulously crafted to address the challenges posed by real-world conditions and deliver accurate lane segmentation. The proposed framework encompasses a meticulous selection of image processing techniques, tailored algorithms, and comprehensive evaluation strategies. It aspires to contribute towards the advancement of lane detection cum lane keeping assist technologies and their seamless integration into real-world applications using Convolutional Neural Network, ultimately paving the path towards a future of intelligent and autonomous transportation systems.},
        keywords = {Advanced Driver Assistance Systems, ADAS, Lane detection, Convolutional Neural Network CNN, Jetson Nano.},
        month = {August},
        }