World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
37
Citations
7427
World Ranking
10582
National Ranking
1302

Heng-Chao 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 Heng-Chao 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: 194 publications — 44th percentile

44% of scientists in this discipline score the same or lower.

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

Heng-Chao 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 Heng-Chao 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: 37 D-Index — 27th percentile

27% of scientists in this discipline score the same or lower.

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

Overview

Heng-Chao Li is affiliated with Southwest Jiaotong University in China and focuses research on Engineering and Computer Science, with a strong emphasis on Computer Vision and Pattern Recognition, Media Technology, Aerospace Engineering, Atmospheric Science, and Artificial Intelligence.

Their research covers a range of topics related to remote sensing and image processing. These main topics of work include:

  • Remote-Sensing Image Classification
  • Advanced Image Fusion Techniques
  • Remote Sensing and Land Use
  • Advanced Image and Video Retrieval Techniques
  • Advanced Neural Network Applications
  • Synthetic Aperture Radar (SAR) Applications and Techniques
  • Advanced SAR Imaging Techniques

Heng-Chao Li has published extensively in prominent venues. Frequent publication venues are:

  • IEEE Transactions on Geoscience and Remote Sensing
  • arXiv (Cornell University)
  • IEEE Geoscience and Remote Sensing Letters
  • IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
  • SSRN Electronic Journal

Among their recent papers are:

  • Learning Center Probability Map for Detecting Objects in Aerial Images, 2020, IEEE Transactions on Geoscience and Remote Sensing
  • Low-Rank and Sparse Representation for Hyperspectral Image Processing: A review, 2021, IEEE Geoscience and Remote Sensing Magazine
  • Joint Classification of Hyperspectral and LiDAR Data Using Hierarchical Random Walk and Deep CNN Architecture, 2020, IEEE Transactions on Geoscience and Remote Sensing
  • Research Progress on Few-Shot Learning for Remote Sensing Image Interpretation, 2021, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
  • Spatial-Spectral Feature Extraction via Deep ConvLSTM Neural Networks for Hyperspectral Image Classification, 2020, IEEE Transactions on Geoscience and Remote Sensing

They have collaborated frequently with other researchers in the field. Notable coauthors include:

  • Qian Du
  • Nanqing Liu
  • Turgay Çelik
  • Antonio Plaza
  • Wen-Shuai Hu

Best Publications

  • Deep Convolutional Neural Networks for Hyperspectral Image Classification

    Wei Hu;Yangyu Huang;Li Wei;Fan Zhang

  • Learning Center Probability Map for Detecting Objects in Aerial Images

    Jinwang Wang;Wen Yang;Heng-Chao Li;Haijian Zhang

  • 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

  • On the Empirical-Statistical Modeling of SAR Images With Generalized Gamma Distribution

    Heng-Chao Li;Wen Hong;Yi-Rong Wu;Ping-Zhi Fan

  • Research Progress on Few-Shot Learning for Remote Sensing Image Interpretation

    Xian Sun;Bing Wang;Zhirui Wang;Hao Li

  • Data Augmentation for Hyperspectral Image Classification With Deep CNN

    Wei Li;Chen Chen;Mengmeng Zhang;Hengchao Li

  • Joint Classification of Hyperspectral and LiDAR Data Using Hierarchical Random Walk and Deep CNN Architecture

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

  • Key techniques for 5G wireless communications: network architecture, physical layer, and MAC layer perspectives

    Unknown

  • Information Fusion for Classification of Hyperspectral and LiDAR Data Using IP-CNN

    Mengmeng Zhang;Wei Li;Ran Tao;Hengchao Li

  • Spatial–Spectral Feature Extraction via Deep ConvLSTM Neural Networks for Hyperspectral Image Classification

    Wen-Shuai Hu;Heng-Chao Li;Lei Pan;Wei Li

  • Spectral–Spatial Weighted Sparse Regression for Hyperspectral Image Unmixing

    Shaoquan Zhang;Jun Li;Heng-Chao Li;Chengzhi Deng

  • Gabor Feature Based Unsupervised Change Detection of Multitemporal SAR Images Based on Two-Level Clustering

    Heng-Chao Li;Turgay Celik;Nathan Longbotham;William J. Emery

  • Hyperspectral Unmixing Based on Nonnegative Matrix Factorization: A Comprehensive Review

    Unknown

  • A³CLNN: Spatial, Spectral and Multiscale Attention ConvLSTM Neural Network for Multisource Remote Sensing Data Classification

    Heng-Chao Li;Wen-Shuai Hu;Wei Li;Jun Li

  • Hyperspectral Unmixing Using Sparsity-Constrained Deep Nonnegative Matrix Factorization With Total Variation

    Xin-Ru Feng;Heng-Chao Li;Jun Li;Qian Du

  • An Efficient and Flexible Statistical Model Based on Generalized Gamma Distribution for Amplitude SAR Images

    Heng-Chao Li;Wen Hong;Yi-Rong Wu;Ping-Zhi Fan

  • SNR Enhancement in Phase-Sensitive OTDR with Adaptive 2-D Bilateral Filtering Algorithm

    Haijun He;Liyang Shao;Hengchao Li;Wei Pan

  • Hyperspectral Unmixing Using Double Reweighted Sparse Regression and Total Variation

    Rui Wang;Heng-Chao Li;Aleksandra Pizurica;Jun Li

  • Change Detection in Synthetic Aperture Radar Images Using a Dual-Domain Network

    Xiaofan Qu;Feng Gao;Junyu Dong;Qian Du

  • Multi-Aspect-Aware Bidirectional LSTM Networks for Synthetic Aperture Radar Target Recognition

    Fan Zhang;Chen Hu;Qiang Yin;Wei Li

  • Data-Driven Distributed Optical Vibration Sensors: A Review

    Li-Yang Shao;Shuaiqi Liu;Sankhyabrata Bandyopadhyay;Feihong Yu

  • Robust Capsule Network Based on Maximum Correntropy Criterion for Hyperspectral Image Classification

    Heng-Chao Li;Wei-Ye Wang;Lei Pan;Wei Li

  • Discriminant Analysis-Based Dimension Reduction for Hyperspectral Image Classification: A Survey of the Most Recent Advances and an Experimental Comparison of Different Techniques

    Wei Li;Fubiao Feng;Hengchao Li;Qian Du

Frequent Co-Authors

Qian Du
Qian Du Mississippi State University
William J. Emery
William J. Emery University of Colorado Boulder
Wen Yang
Wen Yang Beijing Institute of Technology
Turgay Celik
Turgay Celik University of the Witwatersrand
Wei Li
Wei Li Beijing Institute of Technology
Wenzhi Liao
Wenzhi Liao Ghent University
Antonio Plaza
Antonio Plaza University of Extremadura
Kun Fu
Kun Fu University of Chinese Academy of Sciences
Wilfried Philips
Wilfried Philips Ghent University
Ran Tao
Ran Tao Beijing Institute of Technology

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