Image Error Detection: A Systematic Literature Review

Sunardi Oetama, Raymond and Tjahjana, David and Prasetiawan, Iwan and Anastasia, Catherine (2023) Image Error Detection: A Systematic Literature Review. Image Error Detection: A Systematic Literature Review, 7 (3). pp. 837-846. ISSN E-ISSN: 2623-064x | P-ISSN: 2580-8737

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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.

Item Type:	Article
Keywords:	Image detection technology, Image detection error, Systematic Literature Reviews
Subjects:	000 Computer Science, Information and General Works 000 Computer Science, Information and General Works > 000 Computer Science, Knowledge and Systems 000 Computer Science, Information and General Works > 000 Computer Science, Knowledge and Systems > 000 Computer Science, Information and General Works 000 Computer Science, Information and General Works > 000 Computer Science, Knowledge and Systems > 001 Knowledge > 001.4 Research
Divisions:	Faculty of Engineering & Informatics > Information System
Depositing User:	Iwan Prasetiawan (L00552)
Date Deposited:	20 Mar 2024 03:50
Last Modified:	20 Mar 2024 03:50
URI:	https://kc.umn.ac.id/id/eprint/29696

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