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Article

57 Citations

6,780 Views

18 Pages

Enhancing the Super-Resolution of Medical Images: Introducing the Deep Residual Feature Distillation Channel Attention Network for Optimized Performance and Efficiency

Sabina Umirzakova,
Sevara Mardieva,
Shakhnoza Muksimova,
Shabir Ahmad and
Taegkeun Whangbo

Bioengineering2023, 10(11), 1332;https://doi.org/10.3390/bioengineering10111332

19 November 2023

In the advancement of medical image super-resolution (SR), the Deep Residual Feature Distillation Channel Attention Network (DRFDCAN) marks a significant step forward. This work presents DRFDCAN, a model that innovates traditional SR approaches by in...

(This article belongs to the Special Issue Artificial Intelligence (AI) for Medical Image Processing)

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Article

2 Citations

978 Views

28 Pages

Image Haze Removal Using Dual Dark Channels with the Whale Optimization Algorithm and an Image Regression Model

Cheng-Hsiung Hsieh,
Xin-Rui Lin and
Zhong-Ze Li

Electronics2026, 15(1), 215;https://doi.org/10.3390/electronics15010215

2 January 2026

Recently, image haze removal has gained increasing attention in the field of image restoration. Data-driven and model-based methods are popular among researchers. The dark channel prior prevails in model-based methods, where the model parameters, atm...

(This article belongs to the Special Issue Advanced Research in Technology and Information Systems, 2nd Edition)

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