1 citations · 2 across the 5 of their papers we have counts for
5 papers
NL-CS Net: Deep Learning with Non-Local Prior for Image Compressive Sensing
Shuai Bian, Shouliang Qi, Chen Li +2
Deep learning has been applied to compressive sensing (CS) of images successfully in recent years. However, existing network-based methods are often trained as the black box, in wh…
QS-ADN: Quasi-Supervised Artifact Disentanglement Network for Low-Dose CT Image Denoising by Local Similarity Among Unpaired Data
Yuhui Ruan, Qiao Yuan, Chuang Niu +4
Deep learning has been successfully applied to low-dose CT (LDCT) image denoising for reducing potential radiation risk. However, the widely reported supervised LDCT denoising netw…
Quasi-supervised Learning for Super-resolution PET
Guangtong Yang, Chen Li, Yudong Yao +2
Low resolution of positron emission tomography (PET) limits its diagnostic performance. Deep learning has been successfully applied to achieve super-resolution PET. However, common…
Adaptive Weighted Nonnegative Matrix Factorization for Robust Feature Representation
Tingting Shen, Junhang Li, Can Tong +4
Nonnegative matrix factorization (NMF) has been widely used to dimensionality reduction in machine learning. However, the traditional NMF does not properly handle outliers, so that…
Subspace Nonnegative Matrix Factorization for Feature Representation
Junhang Li, Jiao Wei, Can Tong +6
Traditional nonnegative matrix factorization (NMF) learns a new feature representation on the whole data space, which means treating all features equally. However, a subspace is of…