World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
31
Citations
9291
World Ranking
13350
National Ranking
348

Yuliya Tarabalka 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 Yuliya Tarabalka 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: 142 publications — 23rd percentile

23% of scientists in this discipline score the same or lower.

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

Yuliya Tarabalka 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 Yuliya Tarabalka 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: 31 D-Index — 6th percentile

6% of scientists in this discipline score the same or lower.

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

Overview

Yuliya Tarabalka is affiliated with the French Institute for Research in Computer Science and Automation (INRIA) in France. Their research primarily spans the fields of Computer Science, Engineering, and Environmental Science, with specific contributions in subfields such as Artificial Intelligence, Computer Vision and Pattern Recognition, Environmental Engineering, Ocean Engineering, and Media Technology.

The main topics of Tarabalka's work focus on Remote Sensing and LiDAR Applications, Automated Road and Building Extraction, Geochemistry and Geologic Mapping, Remote-Sensing Image Classification, Remote Sensing in Agriculture, Video Surveillance and Tracking Methods, and Domain Adaptation and Few-Shot Learning.

Frequent co-authors include:

  • Isabelle Manighetti
  • Nicolas Girard
  • Onur Taşar
  • Lionel Mattéo
  • Jean-Michel Gaucel

Tarabalka has published in several prominent venues, with repeated contributions to:

  • arXiv (Cornell University)
  • Zenodo (CERN European Organization for Nuclear Research)
  • The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
  • Remote Sensing
  • IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium

Recent significant papers include:

  • "Tree Crown Delineation Algorithm Based on a Convolutional Neural Network," 2020, Remote Sensing
  • "DAugNet: Unsupervised, Multisource, Multitarget, and Life-Long Domain Adaptation for Semantic Segmentation of Satellite Images," 2020, IEEE Transactions on Geoscience and Remote Sensing
  • "U-Net-Id, an Instance Segmentation Model for Building Extraction from Satellite Images-Case Study in the Joanópolis City, Brazil," 2020, Remote Sensing
  • "Mapping Atlantic rainforest degradation and regeneration history with indicator species using convolutional network," 2020, PLoS ONE
  • "Input Similarity from the Neural Network Perspective," 2021, arXiv (Cornell University)

Best Publications

  • Advances in Spectral-Spatial Classification of Hyperspectral Images

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

  • Convolutional Neural Networks for Large-Scale Remote-Sensing Image Classification

    Emmanuel Maggiori;Yuliya Tarabalka;Guillaume Charpiat;Pierre Alliez

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

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

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

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

  • Can semantic labeling methods generalize to any city? the inria aerial image labeling benchmark

    Emmanuel Maggiori;Yuliya Tarabalka;Guillaume Charpiat;Pierre Alliez

  • Segmentation and classification of hyperspectral images using watershed transformation

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

  • Segmentation and Classification of Hyperspectral Images Using Minimum Spanning Forest Grown From Automatically Selected Markers

    Y Tarabalka;J Chanussot;J A Benediktsson

  • Multiple Spectral–Spatial Classification Approach for Hyperspectral Data

    Yuliya Tarabalka;Jón Atli Benediktsson;Jocelyn Chanussot;James C Tilton

  • High-Resolution Aerial Image Labeling With Convolutional Neural Networks

    Emmanuel Maggiori;Yuliya Tarabalka;Guillaume Charpiat;Pierre Alliez

  • Using the U-net convolutional network to map forest types and disturbance in the Atlantic rainforest with very high resolution images

    Fabien H. Wagner;Alber Sanchez;Yuliya Tarabalka;Rodolfo G. Lotte

  • Fully convolutional neural networks for remote sensing image classification

    Emmanuel Maggiori;Yuliya Tarabalka;Guillaume Charpiat;Pierre Alliez

  • Spectral–Spatial Classification of Hyperspectral Data Based on a Stochastic Minimum Spanning Forest Approach

    K. Bernard;Y. Tarabalka;J. Angulo;J. Chanussot

  • Best Merge Region-Growing Segmentation With Integrated Nonadjacent Region Object Aggregation

    J. C. Tilton;Y. Tarabalka;P. M. Montesano;E. Gofman

  • Real-time anomaly detection in hyperspectral images using multivariate normal mixture models and GPU processing

    Yuliya Tarabalka;Trym Vegard Haavardsholm;Ingebjørg Kåsen;Torbjørn Skauli

  • Incremental Learning for Semantic Segmentation of Large-Scale Remote Sensing Data

    Onur Tasar;Yuliya Tarabalka;Pierre Alliez

  • Tree Crown Delineation Algorithm Based on a Convolutional Neural Network

    Jose R. G. Braga;Vinícius Peripato;Ricardo Dalagnol;Matheus Pinheiro Ferreira

  • Polygonal Building Extraction by Frame Field Learning

    Nicolas Girard;Dmitriy Smirnov;Justin Solomon;Yuliya Tarabalka

  • Can you 'read' tongue movements? Evaluation of the contribution of tongue display to speech understanding

    Pierre Badin;Yuliya Tarabalka;Frédéric Elisei;Gérard Bailly

  • Large-Scale Semantic Classification: Outcome of the First Year of Inria Aerial Image Labeling Benchmark

    Bohao Huang;Kangkang Lu;Nicolas Audeberr;Andrew Khalel

  • A Marker-Based Approach for the Automated Selection of a Single Segmentation From a Hierarchical Set of Image Segmentations

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

  • High-Resolution Semantic Labeling with Convolutional Neural Networks

    Emmanuel Maggiori;Yuliya Tarabalka;Guillaume Charpiat;Pierre Alliez

  • Recurrent Neural Networks to Correct Satellite Image Classification Maps

    Emmanuel Maggiori;Guillaume Charpiat;Yuliya Tarabalka;Pierre Alliez

Frequent Co-Authors

Pierre Alliez
Pierre Alliez French Institute for Research in Computer Science and Automation - INRIA
Jon Atli Benediktsson
Jon Atli Benediktsson University of Iceland
Jocelyn Chanussot
Jocelyn Chanussot Grenoble Alpes University
Isabelle Manighetti
Isabelle Manighetti Centre national de la recherche scientifique, CNRS
Luiz E. O. C. Aragão
Luiz E. O. C. Aragão National Institute for Space Research
Josiane Zerubia
Josiane Zerubia French Institute for Research in Computer Science and Automation - INRIA
Ludovic Brucker
Ludovic Brucker National Oceanic and Atmospheric Administration
Bjoern H. Menze
Bjoern H. Menze University of Zurich
Jacques Malavieille
Jacques Malavieille University of Montpellier

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