2 citations · 2 across the 3 of their papers we have counts for
3 papers
eess.IV2023
Self-supervised Noise2noise Method Utilizing Corrupted Images with a Modular Network for LDCT Denoising
Yuting Zhu, Qiang He, Yudong Yao +1
Deep learning is a very promising technique for low-dose computed tomography (LDCT) image denoising. However, traditional deep learning methods require paired noisy and clean datas…
q-bio.MN2023★ 2 cited
Quadratic Graph Attention Network (Q-GAT) for Robust Construction of Gene Regulatory Networks
Hui Zhang, Xuexin An, Qiang He +4
Gene regulatory relationships can be abstracted as a gene regulatory network (GRN), which plays a key role in characterizing complex cellular processes and pathways. Recently, grap…
cs.LG2022
Improving the Level of Autism Discrimination through GraphRNN Link Prediction
Haonan Sun, Qiang He, Shouliang Qi +2
Dataset is the key of deep learning in Autism disease research. However, due to the few quantity and heterogeneity of samples in current dataset, for example ABIDE (Autism Brain Im…