1 citations · 1 across the 6 of their papers we have counts for
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Closed-Form Nonlocal Shrinkage for Multiplicative Image Denoising and SAR Despeckling
Xuran Hu, Mingzhe Zhu, Djordje Stanković +4
Multiplicative noise poses a challenge in coherent and signal-dependent imaging owing to its intensity-dependent variance and frequently non-Gaussian distribution. We propose a det…
Perturbation on Feature Coalition: Towards Interpretable Deep Neural Networks
Xuran Hu, Mingzhe Zhu, Zhenpeng Feng +2
The inherent "black box" nature of deep neural networks (DNNs) compromises their transparency and reliability. Recently, explainable AI (XAI) has garnered increasing attention from…
Multi-task SAR Image Processing via GAN-based Unsupervised Manipulation
Xuran Hu, Mingzhe Zhu, Ziqiang Xu +2
Generative Adversarial Networks (GANs) have shown tremendous potential in synthesizing a large number of realistic SAR images by learning patterns in the data distribution. Some GA…
SAR Despeckling via Regional Denoising Diffusion Probabilistic Model
Xuran Hu, Ziqiang Xu, Zhihan Chen +3
Speckle noise poses a significant challenge in maintaining the quality of synthetic aperture radar (SAR) images, so SAR despeckling techniques have drawn increasing attention. Desp…