Dehua Liu

According to our database, Dehua Liu authored at least 11 papers between 2012 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

TransCotANet: A Lung Field Image Segmentation Network with Multidimensional Global Feature Dynamic Aggregation.

Xuebin Xu, Muyu Wang, Dehua Liu, Meng Lei, Jun Fu, Yang Jia

Symmetry, August, 2023

Location First Non-Maximum Suppression for Uncovered Muck Truck Detection.

Yuxiang Zhang, Dehua Liu, Chuanpeng Su, Juncheng Liu

IEICE Trans. Fundam. Electron. Commun. Comput. Sci., June, 2023

Lung segmentation in chest X-ray image using multi-interaction feature fusion network.

Xuebin Xu, Meng Lei, Dehua Liu, Muyu Wang, Longbin Lu

IET Image Process., 2023

An Efficient Approach for Discovering Graph Entity Dependencies (GEDs).

Dehua Liu, Selasi Kwashie, Yidi Zhang, Guangtong Zhou, Michael Bewong, Xiaoying Wu, Xi Guo, Keqing He, Zaiwen Feng

CoRR, 2023

2015

An efficient online active learning algorithm for binary classification.

Dehua Liu, Peng Zhang, Qinghua Zheng

Pattern Recognit. Lett., 2015

2013

An iterative SVM approach to feature selection and classification in high-dimensional datasets.

Dehua Liu, Hui Qian, Guang Dai, Zhihua Zhang

Pattern Recognit., 2013

A Nearly Unbiased Matrix Completion Approach.

Dehua Liu, Tengfei Zhou, Hui Qian, Congfu Xu, Zhihua Zhang

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2013

Nonconvex Relaxation Approaches to Robust Matrix Recovery.

Shusen Wang, Dehua Liu, Zhihua Zhang

Proceedings of the IJCAI 2013, 2013

Large-Scale Hierarchical Classification via Stochastic Perceptron.

Dehua Liu, Bojun Tu, Hui Qian, Zhihua Zhang

Proceedings of the Twenty-Seventh AAAI Conference on Artificial Intelligence, 2013

2012

EP-GIG Priors and Applications in Bayesian Sparse Learning.

Zhihua Zhang, Shusen Wang, Dehua Liu, Michael I. Jordan

J. Mach. Learn. Res., 2012

Coherence functions with applications in large-margin classification methods.

Zhihua Zhang, Dehua Liu, Guang Dai, Michael I. Jordan

J. Mach. Learn. Res., 2012