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All Journal G-Tech : Jurnal Teknologi Terapan
Catherine Anastasia
Universitas Multimedia Nusantara, Indonesia
Computer Science & IT Decision Sciences, Operations Research & Management Energy Engineering

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Image Error Detection: A Systematic Literature Review Raymond Oetama; David Tjahjana; Iwan Prasetiawan; Catherine Anastasia
G-Tech: Jurnal Teknologi Terapan Vol 7 No 3 (2023): G-Tech, Vol. 7 No. 3 Juli 2023
Publisher : Universitas Islam Raden Rahmat, Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33379/gtech.v7i3.2494

Abstract

The advancement of technology, as well as the creation of new techniques and methodologies for image analysis, is rapid. However, image detection may face some errors. Image error detection will be discussed in this comprehensive literature review. Throughout the papers, this work attempts to learn about the types of images used, algorithms that are frequently used, techniques that are frequently used, and metrics used to test the correctness of the suggested approach. The most commonly used image type is medical images such as Magnetic Resonance Imaging, the algorithm that is widely used is a Convolutional Neural Networks based algorithm. The method that is widely used is a machine learning-based method, and the measurement that is widely used is a Peak Signal Noise Ratio measurement method to measure the accuracy of the algorithm.
Co-Authors David Tjahjana Iwan Prasetiawan Raymond Oetama