114 citations · 147 across the 6 of their papers we have counts for
6 papers
Unsupervised Image Denoising in Real-World Scenarios via Self-Collaboration Parallel Generative Adversarial Branches
Xin Lin, Chao Ren, Xiao Liu +2
Deep learning methods have shown remarkable performance in image denoising, particularly when trained on large-scale paired datasets. However, acquiring such paired datasets for re…
Attention-based 3D CNN with Multi-layer Features for Alzheimer's Disease Diagnosis using Brain Images
Yanteng Zhang, Qizhi Teng, Xiaohai He +4
Structural MRI and PET imaging play an important role in the diagnosis of Alzheimer's disease (AD), showing the morphological changes and glucose metabolism changes in the brain re…
Dual Degradation Representation for Joint Deraining and Low-Light Enhancement in the Dark
Xin Lin, Jingtong Yue, Sixian Ding +3
Rain in the dark poses a significant challenge to deploying real-world applications such as autonomous driving, surveillance systems, and night photography. Existing low-light enha…
Real-World Single Image Super-Resolution: A Brief Review
Honggang Chen, Xiaohai He, Linbo Qing +3
Single image super-resolution (SISR), which aims to reconstruct a high-resolution (HR) image from a low-resolution (LR) observation, has been an active research topic in the area o…
Accurate and Fast reconstruction of Porous Media from Extremely Limited Information Using Conditional Generative Adversarial Network
Junxi Feng, Xiaohai He, Qizhi Teng +3
Porous media are ubiquitous in both nature and engineering applications, thus their modelling and understanding is of vital importance. In contrast to direct acquisition of three-d…
CISRDCNN: Super-resolution of compressed images using deep convolutional neural networks
Honggang Chen, Xiaohai He, Chao Ren +2
In recent years, much research has been conducted on image super-resolution (SR). To the best of our knowledge, however, few SR methods were concerned with compressed images. The S…