Rendering of Impaired Visual Effects on Genesis of Streak - Recognizing Car License Plate

Sathya, K.; Vaidehi, V.; Kavitha, G.

doi:10.1109/aicai.2019.8701308

Cited by 2 publications

(1 citation statement)

References 12 publications

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“…The importance of clean data in the CNN application could not be ignored when [11] combined traditional image processing techniques to filter out unnecessary noises and used CNN at the final stage of car plate recognition, achieving 99.6% accuracy. With that acknowledgement, [26] identified that rain streaks might be one of the big problems of ALPR in a real environment. Thus, they first preprocessed images of noisy rain streak with dictionary learning, then only processed the vehicle LP with CNN.…”

Section: Related Work a Transition Of Alpr To Deep Learning Algorithmmentioning

confidence: 99%

License Plate Detection Using Convolutional Neural Network–Back to the Basic With Design of Experiments

2022

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Automatic License Plate Recognition (ALPR) is one of the applications that hugely benefited from Convolutional Neural Network (CNN) processing which has become the mainstream processing method for complex data. Many ALPR research proposed new CNN model designs and post-processing methods with various levels of performances in ALPR. However, good performing models such as YOLOv3 and SSD in more general object detection and recognition tasks could be effectively transferred to the license plate detection application with a small effort in model tuning. This paper focuses on the design of experiment (DOE) of training parameters in transferring YOLOv3 model design and optimising the training specifically for license plate detection tasks. The parameters are categorised to reduce the DOE run requirements while gaining insights on the YOLOv3 parameter interactions other than seeking optimized train settings. The result shows that the DOE effectively improve the YOLOv3 model to fit the vehicle license plate detection task.

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Section: Related Work a Transition Of Alpr To Deep Learning Algorithmmentioning

confidence: 99%

License Plate Detection Using Convolutional Neural Network–Back to the Basic With Design of Experiments

2022

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Suppressing Rain Streak Weather Noise for Recognizing Overturned Accidental Car Vehicle License Plate

Sathya,

Vaidehi

2023

2023 14th International Conference on Computing Communication and Networking Technologies (ICCCNT)

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Rendering of Impaired Visual Effects on Genesis of Streak - Recognizing Car License Plate

Cited by 2 publications

References 12 publications

License Plate Detection Using Convolutional Neural Network–Back to the Basic With Design of Experiments

License Plate Detection Using Convolutional Neural Network–Back to the Basic With Design of Experiments

Suppressing Rain Streak Weather Noise for Recognizing Overturned Accidental Car Vehicle License Plate

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