3 citations · 6 across the 15 of their papers we have counts for
4 papers · 1 filter
A Tunable Despeckling Neural Network Stabilized via Diffusion Equation
Yi Ran, Zhichang Guo, Jia Li +3
The removal of multiplicative Gamma noise is a critical research area in the application of synthetic aperture radar (SAR) imaging, where neural networks serve as a potent tool. Ho…
Adversarial Transferability in Deep Denoising Models: Theoretical Insights and Robustness Enhancement via Out-of-Distribution Typical Set Sampling
Jie Ning, Jiebao Sun, Shengzhu Shi +4
Deep learning-based image denoising models demonstrate remarkable performance, but their lack of robustness analysis remains a significant concern. A major issue is that these mode…
Perturbation Towards Easy Samples Improves Targeted Adversarial Transferability
Junqi Gao, Biqing Qi, Yao Li +4
The transferability of adversarial perturbations provides an effective shortcut for black-box attacks. Targeted perturbations have greater practicality but are more difficult to tr…
Diffusion Probabilistic Multi-cue Level Set for Reducing Edge Uncertainty in Pancreas Segmentation
Yue Gou, Yuming Xing, Shengzhu Shi +1
Accurately segmenting the pancreas remains a huge challenge. Traditional methods encounter difficulties in semantic localization due to the small volume and distorted structure of…