SwinLightGAN a study of low-light image enhancement algorithms using depth residuals and transformer techniques
Abstract Contemporary algorithms for enhancing images in low-light conditions prioritize improving brightness and contrast but often neglect improving image details. This study introduces the Swin Transformer-based Light-enhancing Generative Adversarial Network (SwinLightGAN), a novel generative adv...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-04-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-025-95329-8 |
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