83 citations · 340 across the 30 of their papers we have counts for
44 papers
A Learnable Optimization and Regularization Approach to Massive MIMO CSI Feedback
Zhengyang Hu, Guanzhang Liu, Qi Xie +3
Channel state information (CSI) plays a critical role in achieving the potential benefits of massive multiple input multiple output (MIMO) systems. In frequency division duplex (FD…
KXNet: A Model-Driven Deep Neural Network for Blind Super-Resolution
Jiahong Fu, Hong Wang, Qi Xie +3
Although current deep learning-based methods have gained promising performance in the blind single image super-resolution (SISR) task, most of them mainly focus on heuristically co…
Decoupled-and-Coupled Networks: Self-Supervised Hyperspectral Image Super-Resolution with Subpixel Fusion
Danfeng Hong, Jing Yao, Deyu Meng +2
Enormous efforts have been recently made to super-resolve hyperspectral (HS) images with the aid of high spatial resolution multispectral (MS) images. Most prior works usually perf…
Two-Stream Graph Convolutional Network for Intra-oral Scanner Image Segmentation
Yue Zhao, Lingming Zhang, Yang Liu +6
Precise segmentation of teeth from intra-oral scanner images is an essential task in computer-aided orthodontic surgical planning. The state-of-the-art deep learning-based methods…
Diagnosing Batch Normalization in Class Incremental Learning
Minghao Zhou, Quanziang Wang, Jun Shu +2
Extensive researches have applied deep neural networks (DNNs) in class incremental learning (Class-IL). As building blocks of DNNs, batch normalization (BN) standardizes intermedia…
Low-light Image Enhancement by Retinex Based Algorithm Unrolling and Adjustment
Xinyi Liu, Qi Xie, Qian Zhao +2
Motivated by their recent advances, deep learning techniques have been widely applied to low-light image enhancement (LIE) problem. Among which, Retinex theory based ones, mostly f…