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Qiangqiang Yuan

Qiangqiang Yuan

Wuhan University
China

D-Index & Metrics

Computer Science

D-Index
59
Citations
13690
World Ranking
3431
National Ranking
461

Qiangqiang Yuan publication distribution in Computer Science in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Computer Science in 2026. The highlighted bar marks where Qiangqiang Yuan sits on this spectrum.

32–41 publications: 7 scientists 42–51 publications: 22 scientists 52–61 publications: 82 scientists 62–71 publications: 134 scientists 72–81 publications: 249 scientists 82–91 publications: 324 scientists 92–101 publications: 421 scientists 102–111 publications: 420 scientists 112–121 publications: 497 scientists 122–131 publications: 544 scientists 132–141 publications: 555 scientists 142–151 publications: 609 scientists 152–161 publications: 559 scientists 162–171 publications: 534 scientists 172–181 publications: 556 scientists 182–191 publications: 583 scientists 192–201 publications: 519 scientists 202–211 publications: 508 scientists 212–221 publications: 490 scientists 222–231 publications: 437 scientists 232–241 publications: 423 scientists 242–251 publications: 408 scientists 252–261 publications: 377 scientists 262–271 publications: 301 scientists 272–281 publications: 335 scientists 282–291 publications: 320 scientists 292–301 publications: 293 scientists 302–311 publications: 250 scientists 312–321 publications: 238 scientists 322–331 publications: 206 scientists 332–341 publications: 209 scientists 342–351 publications: 208 scientists 352–361 publications: 162 scientists 362–371 publications: 176 scientists 372–381 publications: 127 scientists 382–391 publications: 158 scientists 392–401 publications: 128 scientists 402–411 publications: 104 scientists 412–421 publications: 94 scientists 422–431 publications: 99 scientists 432–441 publications: 83 scientists 442–451 publications: 108 scientists 452–461 publications: 73 scientists 462–471 publications: 77 scientists 472–481 publications: 69 scientists 482–491 publications: 84 scientists 492–501 publications: 62 scientists 502–511 publications: 54 scientists 512–521 publications: 57 scientists 522–531 publications: 51 scientists 532–541 publications: 51 scientists 542–551 publications: 32 scientists 552–561 publications: 38 scientists 562–571 publications: 28 scientists 572–581 publications: 43 scientists 582–591 publications: 33 scientists 592–601 publications: 41 scientists 602–611 publications: 32 scientists 612–621 publications: 28 scientists 622–631 publications: 25 scientists 632–641 publications: 27 scientists 642–651 publications: 17 scientists 652–661 publications: 20 scientists 662–671 publications: 17 scientists 672–681 publications: 15 scientists 682–691 publications: 14 scientists 692–701 publications: 21 scientists 702–711 publications: 13 scientists 712–721 publications: 12 scientists 722–731 publications: 19 scientists 732–741 publications: 14 scientists 742–751 publications: 12 scientists 752–761 publications: 10 scientists 762–771 publications: 10 scientists 772–781 publications: 11 scientists 782–791 publications: 10 scientists 792–801 publications: 11 scientists 802–811 publications: 8 scientists 812–821 publications: 8 scientists 822–831 publications: 7 scientists 832–841 publications: 11 scientists 842–851 publications: 10 scientists 852–861 publications: 5 scientists 862–871 publications: 9 scientists 872–881 publications: 4 scientists 882–891 publications: 6 scientists 892–901 publications: 3 scientists 902–911 publications: 6 scientists 912–921 publications: 3 scientists 922–931 publications: 2 scientists 932–941 publications: 2 scientists 942–951 publications: 2 scientists 952–961 publications: 3 scientists 962–971 publications: 3 scientists 972–981 publications: 3 scientists 982–990 publications: 5 scientists 991+ publications: 100 scientists
32 publications 991+

This scientist: 235 publications — 58th percentile

58% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 991 publications or more.

Qiangqiang Yuan D-index placement in Computer Science in 2026

The chart shows the D-index (discipline H-index) distribution of Computer Science scientists ranked by Research.com in 2026. The highlighted bar marks where Qiangqiang Yuan sits on this spectrum.

30–31 D-Index: 879 scientists 32–33 D-Index: 983 scientists 34–35 D-Index: 918 scientists 36–37 D-Index: 990 scientists 38–39 D-Index: 968 scientists 40–41 D-Index: 907 scientists 42–43 D-Index: 821 scientists 44–45 D-Index: 763 scientists 46–47 D-Index: 689 scientists 48–49 D-Index: 543 scientists 50–51 D-Index: 543 scientists 52–53 D-Index: 518 scientists 54–55 D-Index: 500 scientists 56–57 D-Index: 458 scientists 58–59 D-Index: 400 scientists 60–61 D-Index: 337 scientists 62–63 D-Index: 308 scientists 64–65 D-Index: 292 scientists 66–67 D-Index: 249 scientists 68–69 D-Index: 213 scientists 70–71 D-Index: 192 scientists 72–73 D-Index: 189 scientists 74–75 D-Index: 165 scientists 76–77 D-Index: 139 scientists 78–79 D-Index: 119 scientists 80–81 D-Index: 121 scientists 82–83 D-Index: 113 scientists 84–85 D-Index: 88 scientists 86–87 D-Index: 87 scientists 88–89 D-Index: 75 scientists 90–91 D-Index: 69 scientists 92–93 D-Index: 57 scientists 94–95 D-Index: 46 scientists 96–97 D-Index: 38 scientists 98–99 D-Index: 34 scientists 100–101 D-Index: 36 scientists 102–103 D-Index: 27 scientists 104–105 D-Index: 37 scientists 106–107 D-Index: 18 scientists 108–109 D-Index: 31 scientists 110–111 D-Index: 19 scientists 112–113 D-Index: 16 scientists 114–115 D-Index: 12 scientists 116–117 D-Index: 20 scientists 118–119 D-Index: 15 scientists 120–121 D-Index: 5 scientists 122–123 D-Index: 20 scientists 124–125 D-Index: 8 scientists 126–127 D-Index: 5 scientists 128–129 D-Index: 7 scientists 130 D-Index: 3 scientists 131+ D-Index: 98 scientists
30 D-Index 131+

This scientist: 59 D-Index — 77th percentile

77% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 131 D-Index or more.

Overview

Qiangqiang Yuan is affiliated with Wuhan University in China. Their research primarily focuses on environmental science, engineering, and computer science, with significant contributions in subfields including computer vision and pattern recognition, media technology, atmospheric science, environmental engineering, and global and planetary change.

The main topics covered in Yuan's work involve advanced image fusion techniques, image and signal denoising methods, advanced image processing techniques, remote-sensing image classification, air quality monitoring and forecasting, atmospheric and environmental gas dynamics, and atmospheric chemistry and aerosols.

Yuan has authored several recent notable papers, such as:

  • Deep learning in environmental remote sensing: Achievements and challenges (2020), published in Remote Sensing of Environment
  • TTST: A Top-k Token Selective Transformer for Remote Sensing Image Super-Resolution (2024), published in IEEE Transactions on Image Processing
  • EDiffSR: An Efficient Diffusion Probabilistic Model for Remote Sensing Image Super-Resolution (2023), published in IEEE Transactions on Geoscience and Remote Sensing
  • From degrade to upgrade: Learning a self-supervised degradation guided adaptive network for blind remote sensing image super-resolution (2023), published in Information Fusion
  • Thick cloud and cloud shadow removal in multitemporal imagery using progressively spatio-temporal patch group deep learning (2020), published in ISPRS Journal of Photogrammetry and Remote Sensing

Throughout their career, Yuan has collaborated frequently with:

  • Liangpei Zhang
  • Huanfeng Shen
  • Jie Li
  • Jiang He
  • Yuan Wang

Yuan's work has been published extensively in venues such as:

  • IEEE Transactions on Geoscience and Remote Sensing
  • Zenodo (CERN European Organization for Nuclear Research)
  • ISPRS Journal of Photogrammetry and Remote Sensing
  • IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
  • International Journal of Applied Earth Observation and Geoinformation

The research output reflects a continuous focus on remote sensing and advanced computational methods applied to environmental and atmospheric data. Yuan's work demonstrates engagement with image super-resolution, deep learning approaches, and spatio-temporal analysis techniques aimed at addressing challenges in environmental monitoring and data processing.

Best Publications

  • Deep learning in environmental remote sensing: Achievements and challenges

    Qiangqiang Yuan;Huanfeng Shen;Tongwen Li;Zhiwei Li

  • Hyperspectral Image Restoration Using Low-Rank Matrix Recovery

    Hongyan Zhang;Wei He;Liangpei Zhang;Huanfeng Shen

  • Hyperspectral Image Denoising Employing a Spectral–Spatial Adaptive Total Variation Model

    Qiangqiang Yuan;Liangpei Zhang;Huanfeng Shen

  • Image super-resolution

    Linwei Yue;Huanfeng Shen;Jie Li;Qiangqiang Yuan

  • A Multiscale and Multidepth Convolutional Neural Network for Remote Sensing Imagery Pan-Sharpening

    Qiangqiang Yuan;Yancong Wei;Xiangchao Meng;Huanfeng Shen

  • Estimating Ground-Level PM2.5 by Fusing Satellite and Station Observations: A Geo-Intelligent Deep Learning Approach

    Tongwen Li;Huanfeng Shen;Qiangqiang Yuan;Xuechen Zhang

  • Boosting the Accuracy of Multispectral Image Pansharpening by Learning a Deep Residual Network

    Yancong Wei;Qiangqiang Yuan;Huanfeng Shen;Liangpei Zhang

  • Missing Data Reconstruction in Remote Sensing Image With a Unified Spatial–Temporal–Spectral Deep Convolutional Neural Network

    Qiang Zhang;Qiangqiang Yuan;Chao Zeng;Xinghua Li

  • TTST: A Top-k Token Selective Transformer for Remote Sensing Image Super-Resolution

    Unknown

  • Recovering Quantitative Remote Sensing Products Contaminated by Thick Clouds and Shadows Using Multitemporal Dictionary Learning

    Xinghua Li;Huanfeng Shen;Liangpei Zhang;Hongyan Zhang

  • Hyperspectral Image Denoising Employing a Spatial-Spectral Deep Residual Convolutional Neural Network.

    Qiangqiang Yuan;Qiang Zhang;Jie Li;Huanfeng Shen

  • From degrade to upgrade: Learning a self-supervised degradation guided adaptive network for blind remote sensing image super-resolution

    Unknown

  • Learning a Dilated Residual Network for SAR Image Despeckling

    Qiang Zhang;Qiangqiang Yuan;Jie Li;Zhen Yang

  • An effective thin cloud removal procedure for visible remote sensing images

    Huanfeng Shen;Huifang Li;Yan Qian;Liangpei Zhang

  • Point-surface fusion of station measurements and satellite observations for mapping PM2.5 distribution in China: Methods and assessment

    Tongwen Li;Huanfeng Shen;Chao Zeng;Qiangqiang Yuan

  • EDiffSR: An Efficient Diffusion Probabilistic Model for Remote Sensing Image Super-Resolution

    Unknown

  • Cloud removal for remotely sensed images by similar pixel replacement guided with a spatio-temporal MRF model

    Qing Cheng;Huanfeng Shen;Liangpei Zhang;Qiangqiang Yuan

  • Multiframe Super-Resolution Employing a Spatially Weighted Total Variation Model

    Qiangqiang Yuan;Liangpei Zhang;Huanfeng Shen

  • Hyperspectral Image Restoration via Iteratively Regularized Weighted Schatten $p$ -Norm Minimization

    Yuan Xie;Yanyun Qu;Dacheng Tao;Weiwei Wu

  • Hyperspectral Image Denoising Employing a Spatial–Spectral Deep Residual Convolutional Neural Network

    Qiangqiang Yuan;Qiang Zhang;Jie Li;Huanfeng Shen

  • Thick cloud and cloud shadow removal in multitemporal imagery using progressively spatio-temporal patch group deep learning

    Qiang Zhang;Qiangqiang Yuan;Jie Li;Zhiwei Li

  • Cloud Removal with Fusion of High Resolution Optical and SAR Images Using Generative Adversarial Networks

    Jianhao Gao;Qiangqiang Yuan;Jie Li;Hai Zhang

  • Space-time super-resolution for satellite video: A joint framework based on multi-scale spatial-temporal transformer

    Unknown

  • NTIRE 2022 Spectral Recovery Challenge and Data Set

    Unknown

  • A Large-Scale Benchmark Data Set for Evaluating Pansharpening Performance: Overview and Implementation

    Xiangchao Meng;Yiming Xiong;Feng Shao;Huanfeng Shen

  • Hybrid Noise Removal in Hyperspectral Imagery With a Spatial–Spectral Gradient Network

    Qiang Zhang;Qiangqiang Yuan;Jie Li;Xinxin Liu

  • High-quality seamless DEM generation blending SRTM-1, ASTER GDEM v2 and ICESat/GLAS observations

    Linwei Yue;Huanfeng Shen;Liangpei Zhang;Xianwei Zheng

  • Satellite Video Super-Resolution via Multiscale Deformable Convolution Alignment and Temporal Grouping Projection

    Yi Xiao;Xin Su;Qiangqiang Yuan;Denghong Liu

Frequent Co-Authors

Huanfeng Shen
Huanfeng Shen Wuhan University
Liangpei Zhang
Liangpei Zhang Wuhan University
Hongyan Zhang
Hongyan Zhang China University of Geosciences
Michael K. Ng
Michael K. Ng Hong Kong Baptist University
Zhiwei Li
Zhiwei Li Central South University
Pingxiang Li
Pingxiang Li Wuhan University
Dacheng Tao
Dacheng Tao Nanyang Technological University
Zhanqing Li
Zhanqing Li University of Maryland, College Park
Maureen Cribb
Maureen Cribb University of Maryland, College Park
Yuan Xie
Yuan Xie Hong Kong University of Science and Technology

External Links

Personal website of Qiangqiang Yuan Google Scholar page

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Computer Science also provides connections to interdisciplinary fields. For example, with technology increasingly vital in environmental innovation, some students may ask, what jobs can you get with an environmental science degree? Combining computing skills with environmental science can unlock roles in sustainable tech, data analysis, and research.

Best Scientists Citing Qiangqiang Yuan

Liangpei Zhang

Liangpei Zhang

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Publications: 76

Huanfeng Shen

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Wuhan University

Publications: 70

Jocelyn Chanussot

Jocelyn Chanussot

Grenoble Alpes University

Publications: 43

Xi-Le Zhao

Xi-Le Zhao

University of Electronic Science and Technology of China

Publications: 40

Ting-Zhu Huang

Ting-Zhu Huang

University of Electronic Science and Technology of China

Publications: 40

Hongyan Zhang

Hongyan Zhang

China University of Geosciences

Publications: 30

Jiayi Ma

Jiayi Ma

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Publications: 22

Jonathan Cheung-Wai Chan

Jonathan Cheung-Wai Chan

Vrije Universiteit Brussel

Publications: 21

Zebin Wu

Zebin Wu

Nanjing University of Science and Technology

Publications: 20

Antonio Plaza

Antonio Plaza

University of Extremadura

Publications: 19

Xiao Xiang Zhu

Xiao Xiang Zhu

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Publications: 18

Junjun Jiang

Junjun Jiang

Harbin Institute of Technology

Publications: 17

Liang-Jian Deng

Liang-Jian Deng

University of Electronic Science and Technology of China

Publications: 17

Naoto Yokoya

Naoto Yokoya

University of Tokyo

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Deyu Meng

Deyu Meng

Xi'an Jiaotong University

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Qian Du

Qian Du

Mississippi State University

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