| A brief survey on no-reference image quality assessment methods for magnetic resonance images I Stępień, M Oszust Journal of Imaging 8 (6), 160, 2022 | 21 | 2022 |
| Fusion of deep convolutional neural networks for no-reference magnetic resonance image quality assessment I Stpień, R Obuchowicz, A Piórkowski, M Oszust Sensors 21 (4), 1043, 2021 | 8 | 2021 |
| Blind image quality assessment of magnetic resonance images with statistics of local intensity extrema M Oszust, M Bielecka, A Bielecki, I Ste, R Obuchowicz, A Piórkowski Information Sciences 606, 112-125, 2022 | 7 | 2022 |
| No-reference quality assessment of pan-sharpening images with multi-level deep image representations I Stępień, M Oszust Remote Sensing 14 (5), 1119, 2022 | 4 | 2022 |
| No-Reference Image Quality Assessment of Magnetic Resonance images with multi-level and multi-model representations based on fusion of deep architectures I Stępień, M Oszust Engineering Applications of Artificial Intelligence 123, 106283, 2023 | 2 | 2023 |
| Three-branch neural network for No-Reference Quality assessment of Pan-Sharpened Images I Stępień, M Oszust Engineering Applications of Artificial Intelligence 139, 109594, 2025 | | 2025 |
| TIQA-PSI: Toolbox for perceptual Image Quality Assessment of Pan-Sharpened Images I Stępień, M Oszust SoftwareX 23, 101494, 2023 | | 2023 |
Mariusz OszustRzeszow University of Technology在 kia.prz.edu.pl 的电子邮件经过验证
Mariusz OszustRzeszow University of Technology在 kia.prz.edu.pl 的电子邮件经过验证