World's Best Scientists 2026 revealed!
Jocelyn Chanussot

Jocelyn Chanussot

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Computer Science
France
2026

D-Index & Metrics

Computer Science

D-Index
112
Citations
54046
World Ranking
207
National Ranking
6

Jocelyn Chanussot 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 Jocelyn Chanussot 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: 803 publications — 99th percentile

99% of scientists in this discipline score the same or lower.

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

Jocelyn Chanussot 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 Jocelyn Chanussot 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: 112 D-Index — 99th percentile

99% of scientists in this discipline score the same or lower.

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

Research.com Recognitions

  • 2026 - Research.com Computer Science in France Leader Award
  • 2025 - Research.com Computer Science in France Leader Award
  • 2023 - Research.com Computer Science in France Leader Award
  • 2022 - Research.com Computer Science in France Leader Award
  • 2012 - IEEE Fellow For contributions to data fusion and image processing for remote sensing

Overview

Jocelyn Chanussot is affiliated with Grenoble Alpes University in France. Their research primarily focuses on engineering and computer science, with significant contributions in media technology, computer vision and pattern recognition, atmospheric science, artificial intelligence, and aerospace engineering.

The main topics of Chanussot's work include:

  • Remote-Sensing Image Classification
  • Advanced Image Fusion Techniques
  • Remote Sensing and Land Use
  • Image and Signal Denoising Methods
  • Advanced Image and Video Retrieval Techniques
  • Remote Sensing in Agriculture
  • Sparse and Compressive Sensing Techniques

Chanussot has published extensively in several key venues. The most frequent publication outlets feature:

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

Recent papers include:

  • Graph Convolutional Networks for Hyperspectral Image Classification, 2020, IEEE Transactions on Geoscience and Remote Sensing
  • More Diverse Means Better: Multimodal Deep Learning Meets Remote-Sensing Imagery Classification, 2020, IEEE Transactions on Geoscience and Remote Sensing
  • SpectralFormer: Rethinking Hyperspectral Image Classification with Transformers, 2021, arXiv (Cornell University)
  • UIU-Net: U-Net in U-Net for Infrared Small Object Detection, 2022, IEEE Transactions on Image Processing
  • SpectralGPT: Spectral Remote Sensing Foundation Model, 2024, IEEE Transactions on Pattern Analysis and Machine Intelligence

Frequent coauthors in Chanussot's research include:

  • Danfeng Hong
  • Lianru Gao
  • Jing Yao
  • Bing Zhang
  • Gemine Vivone

Chanussot has also contributed to book publications, notably:

  • Hyperspectral Image Analysis, 2020, published by Springer International Publishing

In recognition of their contributions to the field, Chanussot was named an IEEE Fellow in 2012 for work related to data fusion and image processing in remote sensing.

Best Publications

  • Hyperspectral Unmixing Overview: Geometrical, Statistical, and Sparse Regression-Based Approaches

    J. M. Bioucas-Dias;A. Plaza;N. Dobigeon;M. Parente

  • Hyperspectral Remote Sensing Data Analysis and Future Challenges

    J. M. Bioucas-Dias;A. Plaza;G. Camps-Valls;P. Scheunders

  • Recent Advances in Techniques for Hyperspectral Image Processing

    Antonio Plaza;Jon Atli Benediktsson;Joseph W. Boardman;Jason Brazile

  • Advances in Spectral-Spatial Classification of Hyperspectral Images

    M. Fauvel;Y. Tarabalka;J. A. Benediktsson;J. Chanussot

  • Spectral and Spatial Classification of Hyperspectral Data Using SVMs and Morphological Profiles

    M. Fauvel;J.A. Benediktsson;J. Chanussot;J.R. Sveinsson

  • A Critical Comparison Among Pansharpening Algorithms

    Gemine Vivone;Luciano Alparone;Jocelyn Chanussot;Mauro Dalla Mura

  • Graph Convolutional Networks for Hyperspectral Image Classification

    Danfeng Hong;Lianru Gao;Jing Yao;Bing Zhang

  • More Diverse Means Better: Multimodal Deep Learning Meets Remote-Sensing Imagery Classification

    Danfeng Hong;Lianru Gao;Naoto Yokoya;Jing Yao

  • SpectralFormer: Rethinking Hyperspectral Image Classification with Transformers

    Danfeng Hong;Zhu Han;Jing Yao;Lianru Gao

  • More Diverse Means Better: Multimodal Deep Learning Meets Remote Sensing Imagery Classification

    Danfeng Hong;Lianru Gao;Naoto Yokoya;Jing Yao

  • Comparison of Pansharpening Algorithms: Outcome of the 2006 GRS-S Data-Fusion Contest

    L.. Alparone;L.. Wald;J.. Chanussot;C.. Thomas

  • UIU-Net: U-Net in U-Net for Infrared Small Object Detection

    Unknown

  • SVM- and MRF-Based Method for Accurate Classification of Hyperspectral Images

    Y Tarabalka;M Fauvel;J Chanussot;J A Benediktsson

  • SpectralGPT: Spectral Remote Sensing Foundation Model

    Unknown

  • Spectral–Spatial Classification of Hyperspectral Imagery Based on Partitional Clustering Techniques

    Y. Tarabalka;J.A. Benediktsson;J. Chanussot

  • Hyperspectral Pansharpening: A Review

    Laetitia Loncan;Luis B. de Almeida;Jose M. Bioucas-Dias;Xavier Briottet

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

    Behnood Rasti;Danfeng Hong;Renlong Hang;Pedram Ghamisi

  • A Convex Formulation for Hyperspectral Image Superresolution via Subspace-Based Regularization

    Miguel Simoes;Jose Bioucas-Dias;Luis B. Almeida;Jocelyn Chanussot

  • Synthesis of Multispectral Images to High Spatial Resolution: A Critical Review of Fusion Methods Based on Remote Sensing Physics

    C. Thomas;T. Ranchin;L. Wald;J. Chanussot

  • Segmentation and classification of hyperspectral images using watershed transformation

    Y. Tarabalka;J. Chanussot;J. A. Benediktsson

  • Hyperspectral and Multispectral Data Fusion: A comparative review of the recent literature

    Naoto Yokoya;Claas Grohnfeldt;Jocelyn Chanussot

  • Scene Classification With Recurrent Attention of VHR Remote Sensing Images

    Qi Wang;Shaoteng Liu;Jocelyn Chanussot;Xuelong Li

  • Deep learning in multimodal remote sensing data fusion: A comprehensive review

    Unknown

  • Classification of Hyperspectral Images by Using Extended Morphological Attribute Profiles and Independent Component Analysis

    Mauro Dalla Mura;A Villa;J A Benediktsson;J Chanussot

  • Hyperspectral Image Classification With Independent Component Discriminant Analysis

    A. Villa;J. A. Benediktsson;J. Chanussot;C. Jutten

  • A convex formulation for hyperspectral image superresolution via subspace-based regularization

    Miguel Simões;José Bioucas-Dias;Luis B. Almeida;Jocelyn Chanussot

Frequent Co-Authors

Jon Atli Benediktsson
Jon Atli Benediktsson University of Iceland
Mauro Dalla Mura
Mauro Dalla Mura Grenoble Alpes University
Gemine Vivone
Gemine Vivone National Research Council (CNR)
Christian Jutten
Christian Jutten Grenoble Alpes University
Danfeng Hong
Danfeng Hong Chinese Academy of Sciences
Naoto Yokoya
Naoto Yokoya University of Tokyo
Antonio Plaza
Antonio Plaza University of Extremadura
Peijun Du
Peijun Du Nanjing University
Jose M. Bioucas-Dias
Jose M. Bioucas-Dias Instituto Superior Técnico
Paolo Gamba
Paolo Gamba University of Pavia

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