Light weighted Convolutional Neural Network for License Plate Recognition

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Vibha Pandey, et. al


To achieve significant outcomes in license plate recognition is always a challenging task for the researchers. This paper proposes a light weight convolutional neural network without initialsegmentation of characters. Mainly, this work is inspired by current revolutionsindeepneuralnetworks. Further, it alsodoes a good jobin real-timewithaccuracyof recognitionfit for96%forIndian plates on GPU (Graphics Processing Units) and Multicore CPUs. For the training point of view endwise, light weighted convolutional neural network model have been proposed. Main advantage of this model is that it doesn’t uses RNN (Recurrent Neural Network).  The proposed method further can be implemented to produce embedded solutions for license plate recognition systems that feature high level precision on challenging Indian license plates as well.


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How to Cite
et. al, V. P. . (2021). Light weighted Convolutional Neural Network for License Plate Recognition. Turkish Journal of Computer and Mathematics Education (TURCOMAT), 12(12), 4119–4125.