activity
20172024
most cited3DMNDT:3D multi-view registration method based on the normal distributions transform

3 citations · 6 across the 10 of their papers we have counts for

collaborators

15 papers

cs.IR2022

Transition Information Enhanced Disentangled Graph Neural Networks for Session-based Recommendation

Ansong Li

Session-based recommendation is a practical recommendation task that predicts the next item based on an anonymous behavior sequence, and its performance relies heavily on the trans…

cs.LG20211 cited

CRT-Net: A Generalized and Scalable Framework for the Computer-Aided Diagnosis of Electrocardiogram Signals

Jingyi Liu, Zhongyu Li, Xiayue Fan +5

Electrocardiogram (ECG) signals play critical roles in the clinical screening and diagnosis of many types of cardiovascular diseases. Despite deep neural networks that have been gr…

cs.CV20213 cited

3DMNDT:3D multi-view registration method based on the normal distributions transform

Jihua Zhu, Di Wang, Jiaxi Mu +3

The normal distributions transform (NDT) is an effective paradigm for the point set registration. This method is originally designed for pair-wise registration and it will suffer f…

cs.CV2020

Effective multi-view registration of point sets based on student's t mixture model

Yanlin Ma, Jihua Zhu, Zhongyu Li +2

Recently, Expectation-maximization (EM) algorithm has been introduced as an effective means to solve multi-view registration problem. Most of the previous methods assume that each…

cs.LG2020

Multi-view Subspace Clustering Networks with Local and Global Graph Information

Qinghai Zheng, Jihua Zhu, Yuanyuan Ma +2

This study investigates the problem of multi-view subspace clustering, the goal of which is to explore the underlying grouping structure of data collected from different fields or…

cs.CV2020

Graph Neural Networks for UnsupervisedDomain Adaptation of Histopathological ImageAnalytics

Dou Xu, Chang Cai, Chaowei Fang +3

Annotating histopathological images is a time-consuming andlabor-intensive process, which requires broad-certificated pathologistscarefully examining large-scale whole-slide images…