2022 IEEE 16th International Conference on Advanced Trends in Radioelectronics, Telecommunications and Computer Engineering (TC 2022
DOI: 10.1109/tcset55632.2022.9766942
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Analysis of classification quality of DAT-based compression images

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Cited by 2 publications
(4 citation statements)
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“…This can be compression ratio obtained for the considered image or quantization step with which the image has been compressed. This means that the compressed image quality characterized by peak signal-tonoise ratio (PSNR) or other metrics (e.g., mean square error or mean absolute deviation of introduced distortions) can be predicted with quite high accuracy [18,20] for a used technique.…”
Section: Problem Statement and Solution Methodology A Problem Statementmentioning
confidence: 99%
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“…This can be compression ratio obtained for the considered image or quantization step with which the image has been compressed. This means that the compressed image quality characterized by peak signal-tonoise ratio (PSNR) or other metrics (e.g., mean square error or mean absolute deviation of introduced distortions) can be predicted with quite high accuracy [18,20] for a used technique.…”
Section: Problem Statement and Solution Methodology A Problem Statementmentioning
confidence: 99%
“…suppressed by lossy compression. At the same time, in most cases, the probability of correct classification usually reduces if the introduced distortions become larger [18,20].…”
Section: Problem Statement and Solution Methodology A Problem Statementmentioning
confidence: 99%
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