Yingjie Gu    ӭ

Ph. D Candidate

Address:    School of Computer Science & Engineering

                  Nanjing University of Science & Technology

                  Nanjing, 210094, China

Office :     Rm 4053, Computer Science Building

Email :     csyjgu at gmail dot com



Education    Research    Publications    Links

Education

2010.09 - 2015.06

Ph.D. in Pattern Recognition and Intelligence System, Department of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China

2013.07 - 2014.08

Visiting Scholar in Department of Electrical Engineering, Idaho State University, Pocatello, U.S.

2012.12 - 2013.06

Visiting Scholar in Department of Computer Science and Engineering, University of Notre Dame, South Bend, U.S.

2006.09 - 2010.06

B.Sc., in Mathematics, Department of Mathematics, Nanjing University of Science and Technology, Nanjing, China

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Research

I have broad interests in pattern recognition, machine learning and computer vision. Currently, I am interested in the following topics and related application areas.

  • Active Learning, Semi-supervised Learning

  • Image Classification

  • Environmental Perception, Terrain classification

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Publications

Journal Article:

  1. Yingjie Gu, Zhong Jin. Neighborhood Preserving D-Optimal Design for Active Learning and Its Application to Terrain Classification. Neural Computing and Applications, 2013, 23(7-8): 2085-2092.

  2. Yingjie Gu, Zhong Jin, and Steve C. Chiu. Active Learning Combining Uncertainty and Diversity for Multi-Class Image Classification. IET Computer Vision, 2015, 9(3): 400-407.

  3. Yingjie Gu, Zhong Jin. Terrain Classification based on Visible and Infrared Data Fusion. Computer Engineering, 2013, 39(2): 187-191.(Chinese)

Conference Paper:

  1. Yingjie Gu, Zhong Jin, and Steve C. Chiu. Active Learning with Maximum Density and Minimum Redundancy. International Conference on Neural Information Processing (ICONIP). 2014: 103-110.

  2. Yingjie Gu, Zhong Jin, and Steve C. Chiu. Combining Active Learning and Semi-Supervised Learning Using Local and Global Consistency. International Conference on Neural Information Processing (ICONIP). 2014: 215-222.

  3. Yingjie Gu, Zhong Jin. Grass Detection Based on Color Features. CCPR2010, ChongQing, 2010, 2: 687-691. (Chinese)

  4. Yingjie Gu, Dawid Zydek, and Zhong Jin. Active Learning Based on Random Forest and Its Application to Terrain Classification. International Conference on Systems Engineering. 2015: 273-278.

  5. Yingjie Gu and Dawid Zydek. Active Learning for Intrusion Detection. National Wireless Research Collaboration Symposium (NWRCS). 2014: 117-122.

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Links

Some resources for research:

Code

Paper Search

Paper Submission Instruction

Groups & Scholars

Database

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Last modified on 2015-06-26