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Djarot Hindarto
Student S2 Pradita University Batch 3
Computer Science & IT

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Journal : Jurnal Inovasi Informatika

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Plat Nomor Kendaraan dengan Convolution Neural Network Djarot Hindarto; Handri Santoso
Jurnal Inovasi Informatika Vol. 6 No. 2 (2021): Jurnal Inovasi Informatika
Publisher : Universitas Pradita

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51170/jii.v6i2.202

Abstract

The development of Deep Learning technology is very good at detecting Objects. One of them is detection on the vehicle number plate. This method can be applied to Computer Vision to process images using DensetNet121, NasNetLarge, VGG16 and VGG19 methods. The most basic difference between Machine Learning and Deep Learning is the inclusion of a Hidden Layer and what distinguishes the Deep Learning process using neurons as a process from input, process to output. Feature extraction is done directly with the Deep Learning process. In terms of time, training models with Deep Learning are very long, when compared to Machine Learning. The dataset comes from Kaggle, then training is carried out with four Deep Learning models, resulting in a model. There are differences in conducting the training process. Before carrying out the Training process, a pre-paration process from the Image Dataset is carried out. The dataset is divided into two parts, the Training Dataset and the Testing Dataset. After the training model is completed, it is continued with the Testing process and measuring the performance of the model's accuracy. The accuracy of the four models resulting from Deep Learning training is also presented
Co-Authors Handri Santoso