World's Best Scientists 2026 revealed!
Nicolas Thome

Nicolas Thome

D-Index & Metrics

Computer Science

D-Index
35
Citations
4993
World Ranking
11732
National Ranking
292

Nicolas Thome 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 Nicolas Thome 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: 150 publications — 27th percentile

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

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

Nicolas Thome 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 Nicolas Thome 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: 35 D-Index — 20th percentile

20% of scientists in this discipline score the same or lower.

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

Overview

Nicolas Thome is affiliated with Sorbonne University in France. Their research contributions lie primarily within the field of Computer Science, with a focus on several related subfields including Computer Vision and Pattern Recognition, Artificial Intelligence, Radiology, Nuclear Medicine and Imaging, Signal Processing, and Statistical and Nonlinear Physics.

Their work encompasses a range of contemporary topics such as Multimodal Machine Learning Applications, Domain Adaptation and Few-Shot Learning, Advanced Image and Video Retrieval Techniques, Anomaly Detection Techniques and Applications, Advanced Neural Network Applications, Image Retrieval and Classification Techniques, and Generative Adversarial Networks and Image Synthesis.

Thome has published extensively in well-known venues. These frequent publication channels include:

  • arXiv (Cornell University)
  • SSRN Electronic Journal
  • IEEE Transactions on Pattern Analysis and Machine Intelligence
  • Computer Vision and Image Understanding
  • 2022 26th International Conference on Pattern Recognition (ICPR)

Collaborations feature prominently in their research profile, with frequent co-authors including Clément Rambour, Matthieu Cord, Elias Ramzi, Nicolas Audebert, and Toby Collins, reflecting a network of partnerships in related research areas.

Recent papers authored or co-authored by Nicolas Thome include:

  • "Augmenting physical models with deep networks for complex dynamics forecasting" (2021), published in Journal of Statistical Mechanics Theory and Experiment
  • "Deep Time Series Forecasting With Shape and Temporal Criteria" (2022), published in IEEE Transactions on Pattern Analysis and Machine Intelligence
  • "Disentangling Physical Dynamics from Unknown Factors for Unsupervised Video Prediction" (2020), published on arXiv (Cornell University)
  • "Probabilistic Time Series Forecasting with Structured Shape and Temporal Diversity" (2020), published on arXiv (Cornell University)
  • "U-Net Transformer: Self and Cross Attention for Medical Image Segmentation" (2021), published on arXiv (Cornell University)

Best Publications

  • MUTAN: Multimodal Tucker Fusion for Visual Question Answering

    Hedi Ben-younes;Remi Cadene;Matthieu Cord;Nicolas Thome

  • WILDCAT: Weakly Supervised Learning of Deep ConvNets for Image Classification, Pointwise Localization and Segmentation

    Thibaut Durand;Taylor Mordan;Nicolas Thome;Matthieu Cord

  • MUREL: Multimodal Relational Reasoning for Visual Question Answering

    Remi Cadene;Hedi Ben-younes;Matthieu Cord;Nicolas Thome

  • Pooling in image representation: The visual codeword point of view

    Sandra Avila;Nicolas Thome;Matthieu Cord;Eduardo Valle

  • Addressing Failure Prediction by Learning Model Confidence

    Charles Corbière;Nicolas Thome;Avner Bar-Hen;Matthieu Cord

  • BLOCK: Bilinear Superdiagonal Fusion for Visual Question Answering and Visual Relationship Detection

    Hedi Ben-younes;Remi Cadene;Nicolas Thome;Matthieu Cord

  • Cross-Modal Retrieval in the Cooking Context: Learning Semantic Text-Image Embeddings

    Micael Carvalho;Rémi Cadène;David Picard;Laure Soulier

  • Recipe recognition with large multimodal food dataset

    Xin Wang;Devinder Kumar;Nicolas Thome;Matthieu Cord

  • WELDON: Weakly Supervised Learning of Deep Convolutional Neural Networks

    Thibaut Durand;Nicolas Thome;Matthieu Cord

  • Disentangling Physical Dynamics From Unknown Factors for Unsupervised Video Prediction

    Vincent Le Guen;Nicolas Thome

  • U-Net Transformer: Self and Cross Attention for Medical Image Segmentation

    Olivier Petit;Nicolas Thome;Clement Rambour;Loic Themyr

  • A Real-Time, Multiview Fall Detection System: A LHMM-Based Approach

    N. Thome;S. Miguet;S. Ambellouis

  • Learning Deep Hierarchical Visual Feature Coding

    Hanlin Goh;Nicolas Thome;Matthieu Cord;Joo-Hwee Lim

  • T-HOG: An effective gradient-based descriptor for single line text regions

    Rodrigo Minetto;Nicolas Thome;Matthieu Cord;Neucimar J. Leite

  • Quadruplet-Wise Image Similarity Learning

    Marc T. Law;Nicolas Thome;Matthieu Cord

  • Shape and Time Distortion Loss for Training Deep Time Series Forecasting Models

    Vincent Le Guen;Nicolas Thome

  • BOSSA: Extended bow formalism for image classification

    S. Avila;N. Thome;M. Cord;E. Valle

  • Dynamic Scene Classification: Learning Motion Descriptors with Slow Features Analysis

    Christian Theriault;Nicolas Thome;Matthieu Cord

  • Augmenting Physical Models with Deep Networks for Complex Dynamics Forecasting

    Vincent Le Guen;Yuan Yin;Jérémie Dona;Ibrahim Ayed

  • Extended Coding and Pooling in the HMAX Model

    C. Theriault;N. Thome;M. Cord

  • A cognitive and video-based approach for multinational License Plate Recognition

    Nicolas Thome;Antoine Vacavant;Lionel Robinault;Serge Miguet

  • Addressing Failure Prediction by Learning Model Confidence

    Charles Corbière;Nicolas Thome;Avner Bar-Hen;Matthieu Cord

  • Gossip training for deep learning

    Michael Blot;David Picard;Matthieu Cord;Nicolas Thome

  • SnooperText: A Text Detection System for Automatic Indexing of Urban Scenes

    Rodrigo Minetto;Nicolas Thome;Matthieu Cord;Neucimar J. Leite

  • Snoopertext: A multiresolution system for text detection in complex visual scenes

    R. Minetto;N. Thome;M. Cord;J. Fabrizio

Frequent Co-Authors

Matthieu Cord
Matthieu Cord Sorbonne University
Luc Soler
Luc Soler University of Strasbourg
Patrick Gallinari
Patrick Gallinari Sorbonne University
Joo-Hwee Lim
Joo-Hwee Lim Agency for Science, Technology and Research
Ludovic Denoyer
Ludovic Denoyer Sorbonne University
Alain Rakotomamonjy
Alain Rakotomamonjy Criteo (France)

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