Han-Bing Qu

According to our database, Han-Bing Qu authored at least 14 papers between 2005 and 2024.

Collaborative distances:

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

2024

ELSTM: An improved long short-term memory network language model for sequence learning.

Zhi Li, Qing Wang, Jia-Qiang Wang, Han-Bing Qu, Jichang Dong, Zhi Dong

Expert Syst. J. Knowl. Eng., June, 2024

2020

Generalized Constraints as A New Mathematical Problem in Artificial Intelligence: A Review and Perspective.

Bao-Gang Hu, Han-Bing Qu

CoRR, 2020

NEWLSTM: An Optimized Long Short-Term Memory Language Model for Sequence Prediction.

Qing Wang, Rongqun Peng, Jia-Qiang Wang, Zhi Li, Han-Bing Qu

IEEE Access, 2020

2017

Probabilistic Model for Robust Affine and Non-Rigid Point Set Matching.

Han-Bing Qu, Jia-Qiang Wang, Bin Li, Ming Yu

IEEE Trans. Pattern Anal. Mach. Intell., 2017

Emergency Events Classification Based on Minsheng Hotline Unbalanced Short-Text.

Li-Yuan Geng, Wei Jin, Han-Bing Qu

Proceedings of the IEEE International Conference on Big Knowledge, 2017

2016

RGB-D saliency detection under Bayesian framework.

Song-Tao Wang, Zhen Zhou, Han-Bing Qu, Bin Li

Proceedings of the 23rd International Conference on Pattern Recognition, 2016

Visual Saliency Detection for RGB-D Images with Generative Model.

Song-Tao Wang, Zhen Zhou, Han-Bing Qu, Bin Li

Proceedings of the Computer Vision - ACCV 2016, 2016

2014

Probabilistic point set matching with Gaussian mixture model.

Han-Bing Qu, Jia-Qiang Wang, Bin Li, Feng Yue, Wei Jin

Proceedings of the 2014 International Joint Conference on Neural Networks, 2014

Robust Point Set Matching under Variational Bayesian Framework.

Han-Bing Qu, Ji-Chao Li, Jia-Qiang Wang, Lin Xiang, Hai-Jun Tao

Proceedings of the 22nd International Conference on Pattern Recognition, 2014

2013

Variational Bayesian level set for image segmentation.

Han-Bing Qu, Lin Xiang, Jia-Qiang Wang, Bin Li, Hai-Jun Tao

Proceedings of the Sixth International Conference on Machine Vision, 2013

2009

A generalized-constraint neural network model: Associating partially known relationships for nonlinear regressions.

Bao-Gang Hu, Han-Bing Qu, Yong Wang, Shuang-Hong Yang

Inf. Sci., 2009

Variational learning for Generalized Associative Functional Networks in modeling dynamic process of plant growth.

Han-Bing Qu, Bao-Gang Hu

Ecol. Informatics, 2009

2007

Variational Bayes Inference for Generalized Associative Functional Networks.

Han-Bing Qu, Bao-Gang Hu

Proceedings of the International Joint Conference on Neural Networks, 2007

2005

Associating Neural Networks with Partially Known Relationships for Nonlinear Regressions.

Bao-Gang Hu, Han-Bing Qu, Yong Wang

Proceedings of the Advances in Intelligent Computing, 2005