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Lupitha, Mariska
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Computer Science & IT

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Super Resolution Generative Adversarial Networks for Image Supervise Learning Lupitha, Mariska; Santoso, Handri
Sinkron : jurnal dan penelitian teknik informatika Vol. 6 No. 2 (2022): Articles Research Volume 6 Issue 2, April 2022
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v7i2.11373

Abstract

The E-Tilang application system has been widely used to support modern traffic, whereas protocol roads in big cities in Indonesia are already widely used. In principle, the plate number detection tool uses image recognition for detection. Image number plates on vehicles cannot always be read clearly, this is what causes the detection method to be a problem if the image plate number is further processed. The method for processing the plate number image uses deep learning and computer vision methods. For the condition of the image plate number that is not clear, the process of improving the image resolution from low resolution to high resolution is carried out, by applying Generative Adversarial Networks. This method consists of two main parts, namely Generate and Discriminator. Generate serves to generate an image and the Discriminator here is to check the image, can the image plate number be read or not? So that if the image plate number cannot be read, then the process is carried out again to the Generator until it is received by the Discriminator to be read. The process does not end here, the results will be carried out in the next process using Convolutional Neural Networks. Where the process is to detect the plate number image according to the classification of the plate number according to the region. The point is that an unclear image becomes clear by increasing the resolution from low resolution to high resolution so that it is easily read by the Convolutional Neural Network (CNN) algorithm so that the image is easily recognized by the CNN Algorithm. This becomes important in the CNN algorithm process because it gets the processed dataset. To produce a good model, preprocessing of the dataset is carried out. So that the model can detect the image well in terms of model performance.
Prototype of movement monitoring Objects using Arduino Nano and SMS Notifications Lupitha, Mariska; Haryono, Haryono
Sinkron : jurnal dan penelitian teknik informatika Vol. 6 No. 2 (2022): Articles Research Volume 6 Issue 2, April 2022
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v7i2.11413

Abstract

Currently, the development of information technology is very rapid, coupled with the development of the internet of things which is also very fast. This encourages many researchers to use information technology devices and internet of things devices to solve problems in the field. The Internet of things is a device that can communicate between one device and another. Currently, there are many internets of things devices that have been used in everything, including Smart Home, Smart Office, Smart Campus, and others. There is a problem, where currently there is a lot of theft of goods or the transfer of goods that are not known by the owner. This problem encourages researchers to conduct research, by making prototypes to be able to find out about objects that have moved. So that the owner of the goods will know, that the goods have moved without notifying the owner. This research is to detect motion sensors using MPU6050. Where the sensor has two functions, namely accelerometer, and gyroscope. Both sensors are able to find the coordinates of the x-axis, y-axis, and z-axis. The most widely used and affordable microcontroller is the Arduino Nano or Arduino Uno. The purpose of this study is to detect motion with the MPU6050 sensor, then the detection results of the x-axis, y-axis, and z-axis are sent via SMS media with the SIM900A device. The use of a prototype has many functions, it can be used to detect falling objects, detect falling motorcycles, and others. This device is equipped with a SIM900A module which functions to transmit coordinate data via Short Message Service (SMS).
Co-Authors Haryono Haryono Santoso, Handri