1 citations · 1 across the 7 of their papers we have counts for
7 papers
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…
GraphNNK -- Graph Classification and Interpretability
Zeljko Bolevic, Milos Brajovic, Isidora Stankovic +1
Graph Neural Networks (GNNs) have become a standard approach for learning from graph-structured data. However, their reliance on parametric classifiers (most often linear softmax l…
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…
Widely Linear Matched Filter: A Lynchpin towards the Interpretability of Complex-valued CNNs
Qingchen Wang, Zhe Li, Zdenka Babic +3
A recent study on the interpretability of real-valued convolutional neural networks (CNNs) {Stankovic_Mandic_2023CNN} has revealed a direct and physically meaningful link with the…
Manifold-based Shapley for SAR Recognization Network Explanation
Xuran Hu, Mingzhe Zhu, Yuanjing Liu +2
Explainable artificial intelligence (XAI) holds immense significance in enhancing the deep neural network's transparency and credibility, particularly in some risky and high-cost s…
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…