Qr code
中文
Ruyi Feng

Associate professor
Master Tutor


Academic Titles : 计算机学院应用系党支部宣传委员
Official Title : 计算机学院青工会委员
Honors and Titles : 第十届青年教师教学竞赛一等奖;
第四届全国高校移动互联网应用开发创新大赛优秀指导老师。

Gender : Female
Alma Mater : 武汉大学
Education Level : Faculty of Higher Institutions
Degree : 博士学位
Status : Employed
School/Department : 计算机学院
Date of Employment : 2016-07-08
Discipline : Spatial information and digital technology Remote sensing science and technology
Business Address : 未来城校区科一楼432
Contact Information : fengryATcugDOTeduDOTcn
Email :
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Personal Profile

Ruyi Feng received the B.S. degree in Geographic Information System from Hunan Normal University, Changsha, China, in 2011, and the M.S. degree in surveying and mapping engineering and the Ph. D. degree in photogrammetry and remote sensing from Wuhan University, Wuhan, China, in 2013 and 2016, respectively.


She has been with the School of Computer Science, China University of Geosciences (Wuhan) since 2016, and is currently an associate Professor. Her research interests include sparse representation, deep learning, hyperspectral image analysis, high-resolution remote sensing understanding, and intelligent interpretation of remote sensing imagery.


Over the past years, she has chaired and participated in more than 10 national projects dealing with remote sensing imagery, such as Major State Basic Research Development Program of China (973 Program), National High Technology Research and Development Program of China (863 Program),  National Natural Science Foundation of China (NSFC), Fundamental Research Funds for the Central University, China University of Geosciences (Wuhan), Open Reaserch of the Key Laboratory of Spectral Imaging Technology, Chinese Academy of Sciences.

Journal Publications:

      [1]      F. Li, R. Feng, W. Han, L. Wang*, “Ensemble model with cascade attention mechanism for high-resolution remote sensing image scene classification,” Optics Express, vol. 28, no. 12, pp. 22358-22387, 2020. (http://doi.org/10.1364/OE.395866) (SCI, IF=3.561)

[2]      W. Han, L. Wang*, R. Feng*, L. Gao, X. Chen, Z. Deng, J. Chen, and P. Liu, “Sample generation based on a supervised Wasserstein generative adversarial network for high-resolution remote-sensing scene classification”, Information Sciences, vol. 539, pp. 177-194, 2020. (SCI, IF=5.910)

[3]      F. Li, R. Feng*, W. Han, L. Wang*, “An augmentation attention mechanism for high-spatial-resolution remote sensing image scene classification”, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (JSTARS), doi: 10.1109/JSTARS.2020.3006241, 2020. (SCI, IF=3.392)

[4]      H. Li, R. Feng*, L. Wang*, Y. Zhong, L. Zhang, “Superpixel-based reweighted low-rank and total variation sparse unmixing for hyperspectral remote sensing imagery”, IEEE Transactions on Geoscience and Remote Sensing, doi: 10.1109/TGRS.2020.2994260, 2020. (SCI, IF=5.630)

[5]      F. Li, R. Feng*, W. Han, and L. Wang*, “High-resolution remote sensing image scene classification via key filter bank based on convolutional neural network”, IEEE Transactions on Geoscience and Remote Sensing, doi: 10.1109/TGRS.2020.2987060, 2020. (SCI, IF=5.630)

[6]      R. Feng, L. Wang*, Y. Zhong, “Joint local block grouping with noise-adjusted principal component analysis for hyperspectral remote sensing imagery sparse unmixing”, Remote Sensing, vol. 11, no. 10, pp. 1223, 2019. (SCI, IF=4.118)

[7]      M. Song, Y. Zhong*, A. Ma, R. Feng, “Multiobjective sparse subpixel mapping for remote sensing imagery,” IEEE Transactions on Geoscience and Remote Sensing, vol. 57, no. 7, pp. 4490-4508, 2019. (SCI, IF=5.630)

[8]      K. Xu, X. Wang, C. Kong*, R. Feng, G. Liu, C. Wu, “Identification of Hydrothermal Alteration Minerals for Exploring Gold Deposits Based on SVM and PCA Using ASTER Data: A Case Study of Gulong,” Remote Sensing, vol. 11, no. 24, pp. 3003, 2019. (SCI, IF=4.118)

[9]      D. AL-Alimi, Y. Shao, R. Feng, M. A. Al-qaness, M. A. Elaziz, S. Kim*, “Multi-scale geospatial object detection based on shallow-deep feature extraction”, Remote Sensing, vol. 11, no. 21, pp. 2525, 2019. (SCI, IF=4.118)

[10]   Z. Chen, Y. Wang, W. Han*, R. Feng*, J. Chen, “An Improved pretraining strategy-based scene classification with deep learning,” IEEE Geoscience and Remote Sensing Letters (GRSL), DOI: 10.1109 / LGRS.2019.2934341,2019. (SCI, IF=3.534)

[11]   R. Feng, L. Wang*, Y. Zhong, “Least angle regression-based constrained sparse unmixing of hyperspectral remote sensing imagery”, Remote Sensing, vol. 10, no. 10, pp. 1546, 2018. (SCI, IF=4.118)

[12]   R. Feng, Y. Zhong*, L. Wang*, and W. Lin*, “Rolling guidance based scale-aware spatial sparse unmixing for hyperspectral remote sensing imagery,” Remote Sensing, vol. 9, no. 12, pp. 1218, 2017. (SCI, IF=4.118)

[13]   W. Han, R. Feng, L. Wang*, Y. Cheng, “A semi-supervised generative framework with deep learning features for high-resolution remote sensing image scene classification,” ISPRS Journal of Photogrammetry and Remote Sensing, vol. 145, pp. 23–43, 2018. (SCI, IF=6.942)

[14]   R. Feng, Y. Zhong*, X. Xu and L. Zhang, “Adaptive sparse subpixel mapping with a total variation model for remote sensing imagery,” IEEE Transactions on Geoscience and Remote Sensing, vol. 54, no. 5, pp. 2855–2872, 2016. (SCI, IF=5.630)

[15]   R. Feng, Y. Zhong*, Y. Wu, D. He, X. Xu and L. Zhang, “Nonlocal total variation subpixel mapping for hyperspectral remote sensing imagery”, Remote Sensing, vol. 8, no. 3, pp. 250, 2016. (SCI, IF=4.118)

[16]   R. Feng, Y. Zhong*, and L. Zhang, “Adaptive spatial regularization sparse unmixing strategy based on joint MAP for hyperspectral remote sensing imagery,” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (JSTARS), vol. 9, no. 12, pp. 5791–5805, 2016. (SCI, IF=3.392)

[17]   Y. Zhong*, X. Wang, L. Zhao, R. Feng, L. Zhang and Y. Xu, “Blind spectral unmixing based on sparse component analysis for hyperspectral remote sensing imagery,” ISPRS Journal of Photogrammetry and Remote Sensing, vol. 119, pp. 49–63, 2016. (SCI, IF=6.942)

[18]   D. He, Y. Zhong*, R. Feng and L. Zhang, “Spatial-temporal subpixel mapping based on swarm intelligence theory”, Remote Sensing, vol. 8, no. 11, pp. 894, 2016. (SCI, IF=4.118)

[19]   R. Feng, Y. Zhong* and L. Zhang, “An improved non-local sparse unmixing algorithm for hyperspectral imagery,” IEEE Geoscience and Remote Sensing Letters (GRSL), vol. 12, no. 4, pp. 915-918, 2015. (SCI, IF=3.534)

[20]   R. Feng, Y. Zhong* and L. Zhang, “Adaptive non-local Euclidean medians sparse unmixing for hyperspectral imagery”, ISPRS Journal of Photogrammetry and Remote Sensing, vol. 97, pp. 9–24, 2014. (SCI, IF=6.942)

[21] Y. Zhong*, R. Feng and L. Zhang, “Non-local sparse unmixing for hyperspectral remote sensing imagery,” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (JSTARS), vol. 7, no. 6, pp. 1889–1909, 2014. (SCI, IF=3.392)

Conference Papers

      [1]       H. Li, R. Feng, L. Wang, Y. Zhong, and L. Zhang, “Superpixel-based spatial constraints sparse unmixing for hyperspectral remote sensing imagery,” IGARSS 2020.

[2]       J. Bai, R. Feng, L. Wang, H. Li, F. Li, Y. Zhong, and L. Zhang, “Semi-supervised hyperspectral unmixing with very deep convolutional neural network,” IGARSS 2020.

[3]       W. Han, R. Feng, L. Wang, F. Li, and L. Wu, “A multi-stage network for improving the sample quality in Aerial image object detection,” IGARSS 2020.

[4]       J. Chen, R. Feng, L. Wang, W. Han, and J. Huang, “Multi-level strategy-based spatial information prediction for spatiotemporal remote sensing imagery fusion,” IGARSS 2020.

[5]       L. Cheng, L. Wang, and R. Feng, “Fractal characteristics and evolution of urban land-use: a case study in Shenzhen city,” IGARSS 2020.

[6]       Y. Wan, Y. Zhong, A. Ma, J. Wang, L. Zhang, and R. Feng, “RSSM-net: Remote sensing image scene classification based on multi-objective neural architecture search,” IGARSS 2020.

[7]       R. Feng, L. Wang and Y. Zhong, “Local block grouping with NAPCA spatial preprocessing for hyperspectral remote sensing imagery sparse unmixing,” in Proc. 2019 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), July 28-August 2, 2019, Yokohama, Japan.

[8]       Z. Liu, R. Feng, L. Wang, Y. Zhong and L. Cao, “D-RESUNET: ResUNet and dilated convolution for high resolution satellite imagery road extraction," in Proc. 2019 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), July 28-August 2, 2019, Yokohama, Japan.

[9]       W. Han, R. Feng, L. Wang and J. Chen, “Supervised generative adversarial network based sample generation for scene classification,” in Proc. 2019 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), July 28-August 2, 2019, Yokohama, Japan.

[10]   R. Fan, L. Wang, R. Feng and Y. Zhu, “Attention based residual network for high-Resolution remote sensing imagery scene classification,” in Proc. 2019 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), July 28-August 2, 2019, Yokohama, Japan.

[11]   Z. Chu, T. Tian, R. Feng and L. Wang, “Sea-land segmentation with RES-UNET and fully connected CRF,” in Proc. 2019 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), July 28-August 2, 2019, Yokohama, Japan.

[12]   R. Feng, T. Tian, X. Li and K. Sun, “Rolling guidance based scaled-aware spatial sparse unmixing for hyperspectral remote sensing imagery,” in Proc. 2018 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), July 22-27, 2018, Valencia, Spain.

[13]   W. Han, R. Feng, L. Wang and L. Gao, “Adaptive Spatial-Scale-Aware Deep Convolutional Neural Network for High-Resolution Remote Sensing Imagery Scene Classification,” in Proc. 2018 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), July 22-27, 2018, Valencia, Spain.

[14]   R. Feng, L. Wang, Y. Zhong and L. Zhang, “Differentiable sparse unmixing based on Bregman divergence for hyperspectral remote sensing imagery,” in Proc. 2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), July23-28, 2017, Fort Worth, TX, USA.

[15]   X. Han, Y. Zhong, R. Feng and L. Zhang, “Robust geospatial object detection based on pre-trained faster R-CNN framework for high spatial resolution imagery,” in Proc. 2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), July 23-28, 2017, Fort Worth, TX, USA.

[16]   R. Feng, D. He, Y. Zhong and L. Zhang, “Sparse representation based subpixel information extraction framework for hyperspectral remote sensing imagery,” in Proc. 2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), July 10–15, 2016, Beijing, China.

[17]   R. Feng, Y. Zhong and L. Zhang, “Complete dictionary online learning for sparse unmixing,” in Proc. 2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), July 10–15, 2016, Beijing, China.

[18]   Y. Zhong, Y. Wu, R. Feng, X. Xu and L. Zhang, “Non-local sub-pixel mapping for hyperspectral imagery,” in Proc. 2015 7th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), June 2-5, 2015, Tokyo, Japan.

[19]   R. Feng, Y. Zhong and L. Zhang, “Non-local Euclidean medians sparse unmixing for hyperspectral remote sensing imagery,” in Proc. 2014 IEEE International Geoscience and Remote Sensing Symposium and 35th Canadian Symposium on Remote Sensing (IGARSS), July 13–18, 2014, Quebec, Canada.

[20]   R. Feng, Y. Zhong and L. Zhang, “An improved weight-calculation non-local sparse unmixing for hyperspectral imagery,” in Proc. 2014 6th workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), June 24–27, 2014, Lausanne, Switzerland.

[21]   X. Xu, Y. Zhong, L. Zhang, H. Zhang and R. Feng, “A unified sub-pixel mapping model integrating spectral unmixing for hyperspectral imagery,” in Proc. 2013 5th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), June 26-28, 2013, Gainesville, FL, USA.

[22] R. Feng, Y. Zhong and L. Zhang, “Non-local sparse spectral unmixing for remote sensing imagery,” in Proc. 2012 4th workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), June 4–7, 2012, Shanghai, China.


Academic Activities 

Ø  2019 IEEE   International Geoscience and Remote Sensing Symposium (IGARSS)

Jul. 26-Aug. 2,   2019, Yokohama, Japan

Ø  2018 IEEE   International Geoscience and Remote Sensing Symposium (IGARSS)

Jul. 22-27,   2018, Valencia, Spain

Ø  2017 IEEE   International Geoscience and Remote Sensing Symposium (IGARSS)

Jul. 23-28,   2017, Fort Worth, Texas, USA

Ø  Convex   Optimization for Signal Processing and Communications, Short Course at  Sun   Yat-Sen University                                       Aug. 3-14, 2015, Guangzhou, China

Ø  IEEE   International Geoscience and Remote Sensing Symposium and 35th   Canadian Symposium on Remote Sensing (IGARSS)                         Jul. 13-18, 2014,   Quebec, Canada

Ø   4th   workshop on Hyperspectral Image and Signal Processing: Evolution in Remote   Sensing (WHISPERS)                                        Jun.   4-7, 2012, Shanghai, China


Hornors, Awards & Certificates:


05/2020, the “Ten Outstanding Young Persons” Award, China University of Geosciences (Wuhan);

01/2019, the 10th Young Teachers’ Teaching Competition, First prize;

09/2018, the “Surveying and Mapping Technology Progress Award”, First prize;

12/2017, the 4th National College Mobile Internet Application Development and Innovation Competition, First prize(Top22/2760), Excellent Instructor;

07/2016, the “CUG Scholar Award”, China University of Geosciences (Wuhan);

05/2016: the “ Excellent Graduate Student Award”, Wuhan University;

10/2015: the “National scholarship”, Wuhan University;

10/2014: the “Guanghua Special Scholarship”, Wuhan University;

05/2013: the “Excellent Graduate Student Award”, Wuhan University;

05/2011: the “Excellent Graduate Student Award”, Wuhan University(5/100);

06/2010: the “National Motivational Scholarship”, Hunan Normal University(5/100);

06/2008: the “National Scholarship”, Hunan Normal University(2/300).


Professional Activities

Ø    Reviewer   of ISPRS   Journal of Photogrammetry and Remote Sensing (ISPRS), IEEE Transactions on   Geoscience and Remote Sensing (TGRS), IEEE Journal of Selected Topics in   Applied Earth Observations and Remote Sensing (JSTARS), Remote Sensing (RS), IEEE   Geoscience and Remote Sensing Letters (GRSL), et al.

Ø  Member of IEEE

Ø Member of CCF









Education Background

  • 2013.9 -- 2016.6

    武汉大学       Remote sensing science and technology       Doctoral Degree       Doctoral Degree

  • 2011.9 -- 2013.6

    Wuhan University       Surveying and Mapping Engineering       Master's Degree       Master's Degree

  • 2007.9 -- 2011.6

    Hunan Normal University       Geographic Information Science       Bachelor's Degree       Bachelor's Degree

Work Experience

  • 2016.7 -- Now

    中国地质大学(武汉)      计算机学院

Social Affiliations

  • VALSE VOOC Member

  • CCF Member

  • IEEE Member

Other Contact Information

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Research Group

Intelligent interpretation and Application of Remote Sensing (IARS)

主要由王力哲教授及冯如意副教授负责指导,由学院优秀的博士研究生、硕士研究生及高年级本科生组成的青年科研突击团队。
主要研究方向包括:高光谱遥感影像分类、分解、降维、目标探测、异常探测;高分辨遥感影像场景理解、分类、目标检测;多源多时相遥感影像多特征融合。
目前,团队优秀的成果已投稿或发表在国际计算机领域顶级会议、期刊以及国际遥感领域顶级会议及期刊;申请并完成了多项遥感智能解译项目。

多源遥感大数据智能处理

团队由王力哲教授作为学术总指导,由计算机学院的青年副教授、副研究员、讲师、博士后组成的具有一定梯度的青年科研团队。
主要研究方向包括:高光谱遥感数据分析与解译、高分辨率遥感图像的多特征表达与融合、高分辨遥感数据智能处理与分析、多角度影像三维匹配与重建、时空大数据智能处理与分析以及无人机遥感智能解译等方向。
目前,研究成果数十项科研成果投稿或发表在国际遥感领域或多媒体应用等顶级期刊;团队合作承担或完成多项国家级及省部级遥感相关项目。

Research Focus

  • 高光谱遥感图像处理
  • 高分遥感图像智能分析与应用
  • 遥感图像深度学习理论研究
  • 稀疏表达理论
  • 城市遥感