World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
76
Citations
25778
World Ranking
1331
National Ranking
52

Pedram Ghamisi 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 Pedram Ghamisi 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: 250 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: 560 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: 424 scientists 242–251 publications: 408 scientists 252–261 publications: 378 scientists 262–271 publications: 300 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: 335 publications — 80th percentile

80% of scientists in this discipline score the same or lower.

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

Pedram Ghamisi 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 Pedram Ghamisi sits on this spectrum.

30–31 D-Index: 879 scientists 32–33 D-Index: 984 scientists 34–35 D-Index: 918 scientists 36–37 D-Index: 990 scientists 38–39 D-Index: 969 scientists 40–41 D-Index: 907 scientists 42–43 D-Index: 821 scientists 44–45 D-Index: 765 scientists 46–47 D-Index: 689 scientists 48–49 D-Index: 543 scientists 50–51 D-Index: 543 scientists 52–53 D-Index: 517 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: 76 D-Index — 91st percentile

91% of scientists in this discipline score the same or lower.

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

Overview

Pedram Ghamisi is affiliated with the Helmholtz-Zentrum Dresden-Rossendorf in Germany. Their research primarily focuses on engineering and computer science, with extensive contributions to media technology, computer vision and pattern recognition, artificial intelligence, atmospheric science, and global and planetary change.

The scientist's work encompasses several main topics, including:

  • Remote-Sensing Image Classification
  • Remote Sensing and Land Use
  • Advanced Image Fusion Techniques
  • Advanced Image and Video Retrieval Techniques
  • Remote Sensing in Agriculture
  • Landslides and related hazards
  • Anomaly Detection Techniques and Applications

Pedram Ghamisi's publication record includes a significant number of papers in frequent venues such as:

  • arXiv (Cornell University) - 36 publications
  • IEEE Transactions on Geoscience and Remote Sensing - 35 publications
  • Remote Sensing - 17 publications
  • IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing - 16 publications
  • IEEE Geoscience and Remote Sensing Magazine - 13 publications

Recent papers by the scientist include:

  • Support Vector Machine Versus Random Forest for Remote Sensing Image Classification: A Meta-Analysis and Systematic Review, 2020, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
  • SpectralGPT: Spectral Remote Sensing Foundation Model, 2024, IEEE Transactions on Pattern Analysis and Machine Intelligence
  • Classification of Hyperspectral and LiDAR Data Using Coupled CNNs, 2020, IEEE Transactions on Geoscience and Remote Sensing
  • COVID-19 Outbreak Prediction with Machine Learning, 2020, Algorithms
  • Hyperspectral Image Classification With Attention-Aided CNNs, 2020, IEEE Transactions on Geoscience and Remote Sensing

The scientist frequently collaborates with colleagues such as Richard Gloaguen, Naoto Yokoya, Amir Mosavi, Behnood Rasti, and Puhong Duan, with multiple joint publications reflecting a consistent co-authorship pattern.

Best Publications

  • Deep Feature Extraction and Classification of Hyperspectral Images Based on Convolutional Neural Networks

    Yushi Chen;Hanlu Jiang;Chunyang Li;Xiuping Jia

  • Deep Learning for Hyperspectral Image Classification: An Overview

    Shutao Li;Weiwei Song;Leyuan Fang;Yushi Chen

  • Deep Recurrent Neural Networks for Hyperspectral Image Classification

    Unknown

  • Support Vector Machine Versus Random Forest for Remote Sensing Image Classification: A Meta-Analysis and Systematic Review

    Mohammadreza Sheykhmousa;Masoud Mahdianpari;Hamid Ghanbari;Fariba Mohammadimanesh

  • Cascaded Recurrent Neural Networks for Hyperspectral Image Classification

    Renlong Hang;Qingshan Liu;Danfeng Hong;Pedram Ghamisi

  • SpectralGPT: Spectral Remote Sensing Foundation Model

    Unknown

  • Advances in Hyperspectral Image and Signal Processing: A Comprehensive Overview of the State of the Art

    Pedram Ghamisi;Naoto Yokoya;Jun Li;Wenzhi Liao

  • Feature Extraction for Hyperspectral Imagery: The Evolution From Shallow to Deep: Overview and Toolbox

    Behnood Rasti;Danfeng Hong;Renlong Hang;Pedram Ghamisi

  • Generative Adversarial Networks for Hyperspectral Image Classification

    Lin Zhu;Yushi Chen;Pedram Ghamisi;Jon Atli Benediktsson

  • Advanced Spectral Classifiers for Hyperspectral Images: A review

    Pedram Ghamisi;Javier Plaza;Yushi Chen;Jun Li

  • Multisource and Multitemporal Data Fusion in Remote Sensing: A Comprehensive Review of the State of the Art

    Pedram Ghamisi;Behnood Rasti;Naoto Yokoya;Qunming Wang

  • Feature Selection Based on Hybridization of Genetic Algorithm and Particle Swarm Optimization

    Pedram Ghamisi;Jon Atli Benediktsson

  • COVID-19 outbreak prediction with machine learning

    Sina F. Ardabili;Amir Mosavi;Pedram Ghamisi;Filip Ferdinand

  • A Survey on Spectral–Spatial Classification Techniques Based on Attribute Profiles

    Pedram Ghamisi;Mauro Dalla Mura;Jon Atli Benediktsson

  • An efficient method for segmentation of images based on fractional calculus and natural selection

    Pedram Ghamisi;Micael S. Couceiro;JóN Atli Benediktsson;Nuno M. F. Ferreira

  • New Frontiers in Spectral-Spatial Hyperspectral Image Classification: The Latest Advances Based on Mathematical Morphology, Markov Random Fields, Segmentation, Sparse Representation, and Deep Learning

    Pedram Ghamisi;Emmanuel Maggiori;Shutao Li;Roberto Souza

  • Classification of Hyperspectral and LiDAR Data Using Coupled CNNs

    Renlong Hang;Zhu Li;Pedram Ghamisi;Danfeng Hong

  • Noise Reduction in Hyperspectral Imagery: Overview and Application

    Behnood Rasti;Paul Scheunders;Pedram Ghamisi;Giorgio Licciardi

  • COVID-19 pandemic prediction for Hungary; A hybrid machine learning approach

    Gergo Pinter;Imre Felde;Amir Mosavi;Pedram Ghamisi

  • Hyperspectral Image Classification With Attention-Aided CNNs

    Renlong Hang;Zhu Li;Qingshan Liu;Pedram Ghamisi

  • Multilevel Image Segmentation Based on Fractional-Order Darwinian Particle Swarm Optimization

    Pedram Ghamisi;Micael S. Couceiro;Fernando M. L. Martins;Jon Atli Benediktsson

  • Unsupervised Spectral–Spatial Feature Learning via Deep Residual Conv–Deconv Network for Hyperspectral Image Classification

    Lichao Mou;Pedram Ghamisi;Xiao Xiang Zhu

  • Hyperspectral Images Classification With Gabor Filtering and Convolutional Neural Network

    Yushi Chen;Lin Zhu;Pedram Ghamisi;Xiuping Jia

  • Invariant Attribute Profiles: A Spatial-Frequency Joint Feature Extractor for Hyperspectral Image Classification

    Danfeng Hong;Xin Wu;Pedram Ghamisi;Jocelyn Chanussot

Frequent Co-Authors

Jon Atli Benediktsson
Jon Atli Benediktsson University of Iceland
Richard Gloaguen
Richard Gloaguen Helmholtz-Zentrum Dresden-Rossendorf
Amir Mosavi
Amir Mosavi Óbuda University
Xiao Xiang Zhu
Xiao Xiang Zhu Technical University of Munich
Shutao Li
Shutao Li Hunan University
Naoto Yokoya
Naoto Yokoya University of Tokyo
Xudong Kang
Xudong Kang Hunan University
Leyuan Fang
Leyuan Fang Hunan University
Danfeng Hong
Danfeng Hong Chinese Academy of Sciences
Antonio Plaza
Antonio Plaza University of Extremadura

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