Name (in pinyin and Chinese): Kang Li

Gender: Male

Date of Birth: 09/18/1986

Place of Birth: Anhui, China

Home Address: Teacher Dormitory 3-6-10, Youyidadao 368, Wuhan 430062, China

Business Address: School of Computer and Information Engineering, Hubei University, Wuhan 430062, China

Work Phone: 862788662509

Mobile Phone: 8613720163814

E-mail: likang@hubu.edu.cn

Research Interest

Computer vision, Object Tracking, Machine Learning

Education – please list all degrees attained, beginning with the most recent

09, 2012 – 12, 2016Wuhan University

Ph.D. & Computer Applications Technology

Researches on Robust Visual Object Tracking Algorithms in Image Sequence

09, 2009 – 06, 2012Central China Normal University

Master & Computer Applications Technology

Animation Interface on Real time Human Controlling Based on Data

09, 2004 – 07, 2008Anhui University

Bachelor & Labor and Social Security

Work Experience – please list all work experience

01, 2017 – PresentHubei University

School of Computer and Information Engineering, Hubei University, Wuhan 430062, China

Assistant professor

Teaching and Researching

Group Memberships

I am a membership of China Computer Federation(CCF), NO. 84168M.

Publications

[1] Li K, He F*, Chen X. Real-time object tracking via compressive feature selection[J]. Frontiers of Computer Science, 2016, 10(4): 689-701.

[2] Li K, He F*, Yu H, et al. A correlative classifiers approach based on particle filter and sample set for tracking occluded target[J]. Applied Mathematics-A Journal of Chinese Universities, 2017, 32(3): 294-312.

[3] Li K, He F*, Yu H. Robust Visual Tracking based on convolutional features with illumination and occlusion handing[J]. journal of computer science and technology, 2018,33(1): 223-236

[4] Li K, He F*, Yu H, Chen X.A Parallel and Robust Object Tracking Approach Synthesizing Adaptive Bayesian Learning and Improved Incremental Subspace Learning[J]. Frontiers of Computer Science. 2017 DOI 10.1007/s11704-018-6442-4

[5] Li K, Li Y M*, Hu X M, Shao F. A robust and accurate object tracking algorithm based on convolutional neural network[J]Acta Electronica Sinica.2017(only accepted)

[6] Li K, He F*, Chen X.Visual tracking algorithm based on MAP multi-subspace incremental learning[J].SCIENTIA SINICA Informationis 46(4), 476-495(2016)

[7] Li K, He F*, Pan YT, Chen X.Multi-Classifier Object Tracking Based on Cluster Similarity.[J]Acta Electronica Sinica.2016,44(4):821-825

[8] Li K, HE Fazhi*, CHEN Xiao, PAN Yiteng, YU Haiping. Real-Time Multi-scale Object Tracking Based on Cluster Similarity[J]. , 2016, 29(3): 229-239.