Dr. Qiang Yin

Associate Professor, M.S. Supervisor

Editor：College of Information Science and Technology Time：2024-11-06

Dr. Qiang Yin


Associate Professor, M.S. Supervisor

member of Information Science and Technology

Email:yinq@mail.buct.edu.cn


Background                                                                  

Qiang Yin, Doctor of Engineering, Associate Professor, M.S. Supervisor. D. degree from the Institute of Electronics, Chinese Academy of Sciences. Used worked at the Institute of Electronics of the Chinese Academy of Sciences and the European Space Agency, and stayed in Beijing University of Chemical Technology as a teacher after postdoctoral station.

As the outstanding young lecturer of Beijing University of Chemical Technology and the leader of the teaching team of Digital Image Processing in College of Information Science and Technology.

Presided over the projects of National Natural Science Foundation of China, Beijing Natural Science Foundation of China, and National Big Science Device-Aerospace Remote Sensing System Polarization Processing Software. As the Co-PI of the Chinese side of the international cooperation program “Dragon Programme” (Phase IV and V) between the Ministry of Science and Technology and ESA,a senior member of IEEE, an expert of ISO (International Organization for Standardization) Geographic Information Technology Committee Working Group, the Asia-Pacific coordinator of IEEE GRSS (Geoscience and Remote Sensing Society) from 2016 to 2020 and the vice president of IEEE WIE (Society of Women Engineers) Beijing Chapter from 2021 to present.

Areas of Research of Expertise

  • Synthetic aperture radar (SAR) image target detection and identification

  • Remote sensing image processing, polarized radar feature extraction and application, intelligent information processing algorithms, scattering modeling and quantitative inversion.

  • M.S. Admission: students majoring in Electronics and Information Engineering/Communication Engineering/Computer Science and Technology/Artificial Intelligence and other related disciplines are welcome to  apply for the program!

  • Academic Master:

  • Information and Communication Engineering (02 Image Interpretation and Intelligent Processing)

  • Computer Science and Technology (03 Research on Image Intelligent Information Processing Algorithm)

  • Professional Master's Degree:

  • Electronic Information (New Generation Electronic Information Technology-02 Remote Sensing Information Processing)

  • Electronic Information (Computer Technology-05 Research on Image Intelligent Information Processing Algorithm)

Teaching         

  • Digital Signal Processing

  • Digital Image Processing

  • Multi-Sensor Information Fusion

  • A Brief History of Information

  • Remote Sensing Image Processing and Applications for postgraduates

Research                                          

Funded Research Projects

The National Natural Science Foundation of China:

  • Polarization SAR Inversion and Change Detection of Salt Lake Parameters (Key Project of National Natural Science Foundation of China)

  • Research on Modeling and Inversion Methods of Soil Moisture Changes Based on Heavy Trajectory Interferometric SAR Phase Information (National Natural Science Foundation of China)

  • Research on the influence of surface humidity change in SAR deformation monitoring of mine foundations (Project of Beijing Natural Science Foundation)

  • Research on Soil Moisture Change Detection of Satellite-Borne Heavy Orbit Interferometric SAR Data (Project of China Postdoctoral Science Foundation)

Five Representative Publications                         

  1. Qiang Yin; Zhiyuan Lin; Wei Hu; Carlos López-Martínez; Jun Ni; and Fan Zhang. “Crop Classification of Multitemporal PolSAR Based on 3-D Attention Mod-ule With ViT,” IEEE Geoscience Remote Sensing Letters, vol. 20, pp. 1–5, 2023, doi: 10.1109/LGRS.2023.3270488.

  2. Qiang Yin; Junlang Li; Yongsheng Zhou; et al. Deliang Xiang & Fan Zhang. Adaptive weighted learning for vegetation contribution in soil moisture inversion using PolSAR data, International Journal of Remote Sensing, 2022, 43:9, 3190-3215.JCR Q2

  3. Jun Ni; Fan Zhang; Qiang Yin; et al. "Random Neighbor Pixel-Block-Based Deep Recurrent Learning for Polarimetric SAR Image Classification," in IEEE Transactions on Geoscience and Remote Sensing, vol. 59, no. 9, pp. 7557-7569, Sept. 2021, doi: 10.1109/TGRS.2020.3037209.

  4. Qiang Yin; Jie Xu; Deliang Xiang*; et al. Polarimetric Decomposition With an Urban Area Descriptor for Compact Polarimetric SAR Data. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021, 14: 10033-10044.

  5. Qiang Yin; Wen Hong; Fan Zhang*; Eric Pottier; Optimal Combination of Polarimetric Features for Vegetation Classification in PolSAR Image, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2019-11-13 , 12(10)：3919-3931.

  6. You Wu; Qiang Yin*; Fan Zhang; GPU-Based Soil Parameter Parallel Inversion for PolSAR Imagery, Asia Pacific Conference on Synthetic Aperture Radar, 2019.11.26-29.

  7. Qiang Yin, Wen Hong, Fan Zhang, Eric Pottier. Analysis of Polarimetric Feature Combination Based on PolSAR Image Classification Performance with Machine Learning Approach, 2018 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Valencia, Spain, July 22-27 2018.

  8. Qiang Yin, Wen Hong*, Yun Lin, Yang Li. Soil Moisture Change Estimation using InSAR Coherence Variations with Preliminary Laboratory Measurements, Science China Information Sciences, 2017, 60(2): 029301: 1-3.