Abstract
Applications of automated number plate recognition (ANPR) technology in the commercial sector has developed rapidly in recent years. The applications of ANPR system such as vehicle parking, toll enforcement, and traffic management are already widely used but not in Indonesia today. In this paper, the Labeling algorithm and a fully connected neural network are used to create an ANPR system for vehicle parking management in Universitas Multimedia Nusantara, Indonesia. The system is built using Java and the Android SDK for the client and PHP for the server. The proposed ANPR system is targeted for Indonesian civilian number plate. Testing shows that the ANPR system has been implemented successfully. Evaluation of the system gives a precision value of 1 and a recall value of 0.78. These values are obtained with hidden layer nodes of 75, 85, and 95. These number of hidden nodes delivers an F-score of 0.88 with the accuracy of 88%.
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Acknowledgements
I really thank and appreciate both of my supervisors Arya Wicaksana and Ni Made Satvika Iswari for their guidance and support on this work. I would also like to extend my thanks to Universitas Multimedia Nusantara for giving me the chance and opportunity to carry out this work.
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Alexander, K., Wicaksana, A., Iswari, N.M.S. (2020). Labeling Algorithm and Fully Connected Neural Network for Automated Number Plate Recognition System. In: Lee, R. (eds) Applied Computing and Information Technology. ACIT 2019. Studies in Computational Intelligence, vol 847. Springer, Cham. https://doi.org/10.1007/978-3-030-25217-5_10
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