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Semi-supervised Learning for Image Quality Assessment Problem
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 186 - Number 9 |
| Year of Publication: 2024 |
| Authors: Tuan Linh Dang, Thuy Ha Hoang, Minh Hoang Cu, Duc Quang Nguyen, Huu Phuc Hoang |
10.5120/ijca2024923435
|
Tuan Linh Dang, Thuy Ha Hoang, Minh Hoang Cu, Duc Quang Nguyen, Huu Phuc Hoang . Semi-supervised Learning for Image Quality Assessment Problem. International Journal of Computer Applications. 186, 9 ( Feb 2024), 9-13. DOI=10.5120/ijca2024923435
Abstract
We live in the 21st century, a period of digital data explosion. Images are one example. Millions of photos are created yearly, so how can we evaluate their quality? In this article, we will introduce SSL algorithms to solve the problem of image quality assessment. We combined the KONIQ-10K and KADIS-700K datasets to create a new dataset and fix the image quality issues in the old datasets. We conducted comprehensive testing on the Vision Transformer in combination with 5 SSL algorithms, and the results we obtained were exceptional. Compared to ViT, ViT combined with the CRMatch algorithm gave outstanding results, with MAE reduced from 0.53 to 0.40.
References
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