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@article{160918,
        author = {S.Lurdhu Jayasree and A.Anisha and Gayathri B and Ishwarya C and Kaviya R},
        title = {A NOVEL DEEP LEARNING BASED ANPR PIPELINE FOR VEHICLE ACCESS CONTROL},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {10},
        number = {2},
        pages = {59-63},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=160918},
        abstract = {Automatic number-plate recognition is a technique that reads car registration plates utilising Open CV and OCR Engine and optical character recognition on photos. In every nation, traffic regulation and identifying the owners of vehicles have become key issues. Finding the owner of a car that travels too fast and against the regulations of the road can be challenging at times. As a result, it is impossible to apprehend and penalise those individuals because the speed of the driving car may prevent traffic officials from retrieving the vehicle's licence plate. Creation of an ANPR (automatic number plate recognition) system. Today, a variety of ANPR technologies are accessible. Although these systems use many approaches, it is still a difficult work since various elements, such as a vehicle's rapid speed, non-uniform number plate, language of the number, and On the total identification rate, changing illumination conditions can have a big impact. Regarding image size, success rate, and processing time as criteria, many ANPR methodologies are discussed. It is recommended that ANPR be expanded.},
        keywords = {ANPR, access control, character recognition, deep learning, OCR.},
        month = {},
        }