This thesis discusses the problem of improving low-qualityimages using machine learning and computer vision technologies. The studyanalyzes the Real-ESRGAN algorithm based on generative adversarial networksand its ability to reduce noise, blur, and compression artifacts. The developed AIImage Studio platform enables users to upload an image, select an enhancementmode, compare the output with the original image, and download the improvedresult. PSNR and SSIM metrics are considered for evaluating image restoration quality. The proposed approach has practical importance for medicaldiagnostics, security systems, digital archives, and satellite image analysis.
| Mualliflar | X.T. Dusanov |
|---|---|
| Jurnal | Management and Economics Scientific Research Journal |
| Nashr sanasi | 2026-05-21 |
| Jild | 3 |
| Son | 3 |
| Betlar | 49-55 |
| Til | O‘zbek |
sun’iy intellekt, mashinali o‘qitish, Real-ESRGAN, superrezolyutsiya, tasvirni tiklash, kompyuterni ko‘rish, PSNR, SSIM.
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