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Gulo, Steven Eduard
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Computer Science & IT

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Enhancing the Quality of Cellular Camera Video With Convolutional Neural Network Tampubolon, Hotman Parsaoran; Sinurat, Watas; Gulo, Steven Eduard; Gulo, Befi Juniman; Husein, Amir Mahmud
Sinkron : jurnal dan penelitian teknik informatika Vol. 4 No. 1 (2019): SinkrOn Volume 4 Number 1, October 2019
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (477.93 KB) | DOI: 10.33395/sinkron.v4i1.10239

Abstract

Abstrak— At present technological developments, especially in the field of computer vision, are showing significant performance such as the application of convolutional neural networks that have a very high degree of accuracy, for example improving video quality which recently has image restoration such as super resolution (VSR) thanks to deep learning with the aim of helping produce better visual videos. The use of video cameras for mobile devices is now increasingly highly developed. Nowadays mobile devices are experiencing a rapid increase in quality especially in cameras. However, physical limitations such as the small sensor size, compact lens and the lack of supporting hardware can prevent cellular devices from achieving good video camera quality results. For that many method approaches are applied, one of which is the CNN (Convolutional Neural Network) method. This method can improve the image of video recordings that have poor quality. Keywords—Convolutional neural network, computer vision, Improved video quality ;
Co-Authors Amir Mahmud Husein, Amir Mahmud Gulo, Befi Juniman Sinurat, Watas Tampubolon, Hotman Parsaoran