activity
20162020
most citedModeling Historical AIS Data For Vessel Path Prediction: A Comprehensive Treatment

31 citations · 91 across the 10 of their papers we have counts for

collaborators

10 papers

eess.IV2020★ 4 cited

Stereo Endoscopic Image Super-Resolution Using Disparity-Constrained Parallel Attention

Tianyi Zhang, Yun Gu, Xiaolin Huang +2

With the popularity of stereo cameras in computer assisted surgery techniques, a second viewpoint would provide additional information in surgery. However, how to effectively acces…

cs.LG2020

End-To-End Graph-based Deep Semi-Supervised Learning

Zihao Wang, Enmei Tu, Zhou Meng

The quality of a graph is determined jointly by three key factors of the graph: nodes, edges and similarity measure (or edge weights), and is very crucial to the success of graph-b…

cs.AI2020★ 31 cited

Modeling Historical AIS Data For Vessel Path Prediction: A Comprehensive Treatment

Enmei Tu, Guanghao Zhang, Shangbo Mao +2

The prosperity of artificial intelligence has aroused intensive interests in intelligent/autonomous navigation, in which path prediction is a key functionality for decision support…

cs.LG2019

Semi-Supervised Deep Learning Using Improved Unsupervised Discriminant Projection

Xiao Han, Zihao Wang, Enmei Tu +2

Deep learning demands a huge amount of well-labeled data to train the network parameters. How to use the least amount of labeled data to obtain the desired classification accuracy…

cs.LG2019★ 17 cited

A Review of Semi Supervised Learning Theories and Recent Advances

Enmei Tu, Jie Yang

Semi-supervised learning, which has emerged from the beginning of this century, is a new type of learning method between traditional supervised learning and unsupervised learning.…

cs.LG2016

A Theoretical Study of The Relationship Between Whole An ELM Network and Its Subnetworks

Enmei Tu, Guanghao Zhang, Lily Rachmawati +2

A biological neural network is constituted by numerous subnetworks and modules with different functionalities. For an artificial neural network, the relationship between a network…