Fengchao Xiong (熊凤超)

Ph.D, Lecturer

Department of Artificial Intelligence, School of Computer Science and Engineering, Nanjing University of Science and Technology

fcxiong@njust.edu.cn | Google Scholar | Github | Blog | Linkedin

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[Biography] [Researh] [Education] [Publications] [Projects] [Awards & Service]

Biography

I join school of computer science and engineering, Nanjing University of Science and Technology in October 2019 as a lecturer. I received my bachelor degree from school of software, Shandong University, in June, 2014. From 2014 to 2019, I studied in the college of computer science, Zhejiang University where I obtained my Ph.D degree in September 2019. I visited Wuhan University as an exchange student from September, 2011 to July, 2012 and Griffith University as a visiting scholar from November 2017 to November 2018. My research lies in computer vision and hyperspectral imaging.

Research

Machine Learning: Computer Vision:

Education

Publication

  1. BAE-Net: a band attention aware ensemble network for hyperspectral object tracking.
    Zhuanfeng Li,Fengchao Xiong (coreresponding author), Jun Zhou, Jing Wang, Jianfeng Lu, Yuntao Qian.
    IEEE International On Image Processing(ICIP), United Arab Emirates, 2020. (Accepted)
  2. Nonlocal Low-rank Nonnegative Tensor Factorization for Hyperspectral Unmixing.
    Fengchao Xiong, Kun Qian, JianFeng Lu, Jun Zhou, Yuntao Qian.
    IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Hawaii, 2020. (Accepted)
  3. Spectral Mixture Model Inspired Network Architectures for Hyperspectral Unmixing.
    Yuntao Qian, Fengchao Xiong, Qipeng Qian, Jun Zhou.
    IEEE Transactions on Geoscience and Remote Sensing (TGRS), 2020. [PDF](Accepted)
  4. Material based object tracking in hyperspectral videos
    Fengchao Xiong, Jun Zhou, Yuntao Qian.
    IEEE Transactions on Image Processing(TIP) vol. 29, no. 1, pp. 3719-3733, 2020.[PDF](Accepted, the first CCF-A ranking paper in my previous lab.)
  5. Dynamic Material-Awarded Object Tracking in Hyperspectral Videos.
    Fengchao Xiong, Jun Zhou, Yuntao Qian, Jocelyn Chanussot.
    IEEE Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), Amsterdam, 2019.
  6. Deep Unfolded Iterative Shrinkage-Thresholding Model for Hyperspectral Unmixing.
    Qipeng Qian, Fengchao Xiong, Jun Zhou.
    IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Yokohama, 2019. [PDF]
  7. Hyperspectral restoration via L0 Gradient Regularized Low-Rank Tensor factorization.
    Fengchao Xiong, Jun Zhou, Yuntao Qian.
    IEEE Transactions on Geoscience and Remote Sensing (TGRS),vol. 57, no. 12, pp. 10410-10425, Dec. 2019. [PDF] [Code]
  8. Hyperspectral Unmixing via Total Variation Regularized Nonnegative Tensor Factorization.
    Fengchao Xiong, Yuntao Qian, Jun Zhou.
    IEEE Transactions on Geoscience and Remote Sensing (TGRS),vol. 57, no. 4, pp. 2341-2357, April 2019 [PDF]
  9. Object Tracking in Hyperspectral Videos with Convolutional Features and Kernelized Correlation Filter.
    Kun Qian, Jun Zhou,Fengchao Xiong,Huixin Zhou,Juan Du.
    International Conference on Smart Multimedia (ICSM), Toulon, 2018, pp. 308-319 [PDF]
  10. Hyperspectral Imagery Denoising via Reweighed Sparse Low-Rank Nonnegative Tensor Factorization.
    Fengchao Xiong, Yuntao Qian, Jun Zhou..
    IEEE International Conference on Image Processing (ICIP), 2018, [PDF]
  11. Superpixel-Based Nonnegative Tensor Factorization for Hyperspectral Unmixing.
    Fengchao Xiong, Jingzhou Chen, Yuntao Qian, Jun Zhou.
    IEEE International Geoscience and Remote Sensing Symposium (IGARSS),Valencia, 2018, pp. 6392-6395. [PDF]
  12. Matrix-Vector Nonnegative Tensor Factorization for Blind Unmixing of Hyperspectral Imagery.
    Yuntao Qian, Fengchao Xiong, Shan Zeng, Jun Zhou, and Yuan Yan Tang
    IEEE Transactions on Geoscience and Remote Sensing (TGRS), , vol. 55, no. 3, pp. 1776-1792, March 2017. [PDF][Code].

Awards & Service

Awards and Honors Reviewer Volunteer

Advising

Master students