activity
20172022
most citedTrusted Multi-View Classification

49 citations · 125 across the 7 of their papers we have counts for

collaborators

9 papers

cs.CV20224 cited

Uncertainty-Aware Multi-View Representation Learning

Yu Geng, Zongbo Han, Changqing Zhang +1

Learning from different data views by exploring the underlying complementary information among them can endow the representation with stronger expressive ability. However, high-dim…

cs.LG202149 cited

Trusted Multi-View Classification

Zongbo Han, Changqing Zhang, Huazhu Fu +1

Multi-view classification (MVC) generally focuses on improving classification accuracy by using information from different views, typically integrating them into a unified comprehe…

cs.LG202022 cited

Deep Partial Multi-View Learning

Changqing Zhang, Yajie Cui, Zongbo Han +3

Although multi-view learning has made signifificant progress over the past few decades, it is still challenging due to the diffificulty in modeling complex correlations among diffe…

cs.CV20203 cited

SPL-MLL: Selecting Predictable Landmarks for Multi-Label Learning

Junbing Li, Changqing Zhang, Pengfei Zhu +3

Although significant progress achieved, multi-label classification is still challenging due to the complexity of correlations among different labels. Furthermore, modeling the rela…

eess.IV202016 cited

M2Net: Multi-modal Multi-channel Network for Overall Survival Time Prediction of Brain Tumor Patients

Tao Zhou, Huazhu Fu, Yu Zhang +4

Early and accurate prediction of overall survival (OS) time can help to obtain better treatment planning for brain tumor patients. Although many OS time prediction methods have bee…

eess.IV2020

Diagnosis of Coronavirus Disease 2019 (COVID-19) with Structured Latent Multi-View Representation Learning

Hengyuan Kang, Liming Xia, Fuhua Yan +8

Recently, the outbreak of Coronavirus Disease 2019 (COVID-19) has spread rapidly across the world. Due to the large number of affected patients and heavy labor for doctors, compute…