World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
67
Citations
17685
World Ranking
2197
National Ranking
298

Wei Li 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 Wei Li 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: 314 publications — 76th percentile

76% of scientists in this discipline score the same or lower.

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

Wei Li 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 Wei Li 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: 67 D-Index — 85th percentile

85% of scientists in this discipline score the same or lower.

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

Overview

Wei Li is affiliated with the Beijing Institute of Technology in China. Their research spans multiple fields, primarily within engineering and computer science, with a strong focus on subfields such as computer vision and pattern recognition, media technology, artificial intelligence, aerospace engineering, and atmospheric science.

Wei Li's work extensively covers topics including remote-sensing image classification, advanced image fusion techniques, remote sensing and land use, advanced neural network applications, domain adaptation and few-shot learning, infrared target detection methodologies, and image and signal denoising methods.

The scientist has contributed to a significant number of publications in prominent venues, including:

  • IEEE Transactions on Geoscience and Remote Sensing
  • arXiv (Cornell University)
  • IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
  • IEEE Transactions on Neural Networks and Learning Systems
  • Remote Sensing

Wei Li's recent papers demonstrate contributions to advanced remote sensing and hyperspectral image classification research. Selected works include:

  • Deep Learning for Unmanned Aerial Vehicle-Based Object Detection and Tracking: A survey, 2021, IEEE Geoscience and Remote Sensing Magazine
  • Graph Information Aggregation Cross-Domain Few-Shot Learning for Hyperspectral Image Classification, 2022, IEEE Transactions on Neural Networks and Learning Systems
  • Topological Structure and Semantic Information Transfer Network for Cross-Scene Hyperspectral Image Classification, 2021, IEEE Transactions on Neural Networks and Learning Systems
  • Deep Cross-Domain Few-Shot Learning for Hyperspectral Image Classification, 2021, IEEE Transactions on Geoscience and Remote Sensing
  • Single-Source Domain Expansion Network for Cross-Scene Hyperspectral Image Classification, 2023, IEEE Transactions on Image Processing

Wei Li frequently collaborates with other researchers whose names appear in multiple co-authored works. Frequent co-authors include Ran Tao, Mengmeng Zhang, Qian Du, Xiang-Gen Xia, and Shou Feng.

Best Publications

  • Hyperspectral Image Classification Using Deep Pixel-Pair Features

    Wei Li;Guodong Wu;Fan Zhang;Qian Du

  • Local Binary Patterns and Extreme Learning Machine for Hyperspectral Imagery Classification

    Wei Li;Chen Chen;Hongjun Su;Qian Du

  • Collaborative Representation for Hyperspectral Anomaly Detection

    Wei Li;Qian Du

  • Multisource Remote Sensing Data Classification Based on Convolutional Neural Network

    Xiaodong Xu;Wei Li;Qiong Ran;Qian Du

  • Diverse Region-Based CNN for Hyperspectral Image Classification

    Mengmeng Zhang;Wei Li;Qian Du

  • Locality-Preserving Dimensionality Reduction and Classification for Hyperspectral Image Analysis

    Wei Li;S. Prasad;J. E. Fowler;L. M. Bruce

  • DeepUNet: A Deep Fully Convolutional Network for Pixel-Level Sea-Land Segmentation

    Ruirui Li;Wenjie Liu;Lei Yang;Shihao Sun

  • Graph Information Aggregation Cross-Domain Few-Shot Learning for Hyperspectral Image Classification.

    Unknown

  • ORSIm Detector: A Novel Object Detection Framework in Optical Remote Sensing Imagery Using Spatial-Frequency Channel Features

    Xin Wu;Danfeng Hong;Jiaojiao Tian;Jocelyn Chanussot

  • HSI-BERT: Hyperspectral Image Classification Using the Bidirectional Encoder Representation From Transformers

    Ji He;Lina Zhao;Hongwei Yang;Mengmeng Zhang

  • Transferred Deep Learning for Anomaly Detection in Hyperspectral Imagery

    Wei Li;Guodong Wu;Qian Du

  • Deep Learning for UAV-based Object Detection and Tracking: A Survey

    Xin Wu;Wei Li;Danfeng Hong;Ran Tao

  • Combined sparse and collaborative representation for hyperspectral target detection

    Wei Li;Qian Du;Bing Zhang

  • Deep Cross-Domain Few-Shot Learning for Hyperspectral Image Classification

    Zhaokui Li;Ming Liu;Yushi Chen;Yimin Xu

  • Topological Structure and Semantic Information Transfer Network for Cross-Scene Hyperspectral Image Classification.

    Yuxiang Zhang;Wei Li;Mengmeng Zhang;Ying Qu

  • Feature Extraction for Classification of Hyperspectral and LiDAR Data Using Patch-to-Patch CNN

    Mengmeng Zhang;Wei Li;Qian Du;Lianru Gao

  • Spectral-Spatial Classification of Hyperspectral Image Based on Kernel Extreme Learning Machine

    Chen Chen;Wei Li;Hongjun Su;Kui Liu

  • Nearest Regularized Subspace for Hyperspectral Classification

    Wei Li;Eric W. Tramel;Saurabh Prasad;James E. Fowler

  • Hyperspectral Anomaly Detection by Fractional Fourier Entropy

    Ran Tao;Xudong Zhao;Wei Li;Heng-Chao Li

  • Low-Rank and Sparse Representation for Hyperspectral Image Processing: A Review

    Jiangtao Peng;Weiwei Sun;Heng-Chao Li;Wei Li

  • Gabor-Filtering-Based Nearest Regularized Subspace for Hyperspectral Image Classification

    Wei Li;Qian Du

  • Land-use scene classification using multi-scale completed local binary patterns

    Chen Chen;Baochang Zhang;Hongjun Su;Wei Li

  • Joint Within-Class Collaborative Representation for Hyperspectral Image Classification

    Wei Li;Qian Du

  • Scene classification using local and global features with collaborative representation fusion

    Jinyi Zou;Wei Li;Chen Chen;Qian Du

Frequent Co-Authors

Qian Du
Qian Du Mississippi State University
Ran Tao
Ran Tao Beijing Institute of Technology
James E. Fowler
James E. Fowler Mississippi State University
Saurabh Prasad
Saurabh Prasad University of Houston
Heng-Chao Li
Heng-Chao Li Southwest Jiaotong University
Lianru Gao
Lianru Gao Aerospace Information Research Institute
Danfeng Hong
Danfeng Hong Chinese Academy of Sciences
Hongjun Su
Hongjun Su Hohai University
Gottfried Kirchengast
Gottfried Kirchengast University of Graz
Juha Hyyppä
Juha Hyyppä Finnish Geospatial Research Institute

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