World's Best Scientists 2026 revealed!

D-Index & Metrics

Engineering and Technology

D-Index
35
Citations
5068
World Ranking
8980
National Ranking
212

Xavier Descombes publication distribution in Engineering and Technology in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Engineering and Technology in 2026. The highlighted bar marks where Xavier Descombes sits on this spectrum.

38–47 publications: 20 scientists 48–57 publications: 35 scientists 58–67 publications: 96 scientists 68–77 publications: 135 scientists 78–87 publications: 190 scientists 88–97 publications: 259 scientists 98–107 publications: 283 scientists 108–117 publications: 369 scientists 118–127 publications: 341 scientists 128–137 publications: 386 scientists 138–147 publications: 372 scientists 148–157 publications: 457 scientists 158–167 publications: 415 scientists 168–177 publications: 407 scientists 178–187 publications: 421 scientists 188–197 publications: 378 scientists 198–207 publications: 403 scientists 208–217 publications: 317 scientists 218–227 publications: 346 scientists 228–237 publications: 321 scientists 238–247 publications: 260 scientists 248–257 publications: 280 scientists 258–267 publications: 240 scientists 268–277 publications: 214 scientists 278–287 publications: 242 scientists 288–297 publications: 203 scientists 298–307 publications: 166 scientists 308–317 publications: 154 scientists 318–327 publications: 175 scientists 328–337 publications: 159 scientists 338–347 publications: 99 scientists 348–357 publications: 131 scientists 358–367 publications: 106 scientists 368–377 publications: 118 scientists 378–387 publications: 97 scientists 388–397 publications: 108 scientists 398–407 publications: 82 scientists 408–417 publications: 71 scientists 418–427 publications: 64 scientists 428–437 publications: 55 scientists 438–447 publications: 54 scientists 448–457 publications: 60 scientists 458–467 publications: 47 scientists 468–477 publications: 40 scientists 478–487 publications: 30 scientists 488–497 publications: 29 scientists 498–507 publications: 38 scientists 508–517 publications: 40 scientists 518–527 publications: 32 scientists 528–537 publications: 23 scientists 538–547 publications: 28 scientists 548–557 publications: 23 scientists 558–567 publications: 19 scientists 568–577 publications: 16 scientists 578–587 publications: 17 scientists 588–597 publications: 18 scientists 598–607 publications: 22 scientists 608–617 publications: 15 scientists 618–627 publications: 9 scientists 628–637 publications: 11 scientists 638–647 publications: 21 scientists 648–657 publications: 12 scientists 658–667 publications: 9 scientists 668–677 publications: 11 scientists 678–687 publications: 9 scientists 688–697 publications: 6 scientists 698–707 publications: 14 scientists 708–717 publications: 7 scientists 718–727 publications: 8 scientists 728–737 publications: 10 scientists 738–747 publications: 9 scientists 748–757 publications: 5 scientists 758–767 publications: 5 scientists 768–777 publications: 11 scientists 778–787 publications: 7 scientists 788–797 publications: 2 scientists 798–803 publications: 4 scientists 804+ publications: 100 scientists
38 publications 804+

This scientist: 269 publications — 69th percentile

69% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 804 publications or more.

Xavier Descombes D-index placement in Engineering and Technology in 2026

The chart shows the D-index (discipline H-index) distribution of Engineering and Technology scientists ranked by Research.com in 2026. The highlighted bar marks where Xavier Descombes sits on this spectrum.

30 D-Index: 59 scientists 31 D-Index: 114 scientists 32 D-Index: 129 scientists 33 D-Index: 189 scientists 34 D-Index: 200 scientists 35 D-Index: 262 scientists 36 D-Index: 311 scientists 37 D-Index: 312 scientists 38 D-Index: 350 scientists 39 D-Index: 385 scientists 40 D-Index: 348 scientists 41 D-Index: 362 scientists 42 D-Index: 426 scientists 43 D-Index: 380 scientists 44 D-Index: 310 scientists 45 D-Index: 341 scientists 46 D-Index: 301 scientists 47 D-Index: 306 scientists 48 D-Index: 271 scientists 49 D-Index: 246 scientists 50 D-Index: 210 scientists 51 D-Index: 253 scientists 52 D-Index: 213 scientists 53 D-Index: 221 scientists 54 D-Index: 195 scientists 55 D-Index: 186 scientists 56 D-Index: 170 scientists 57 D-Index: 167 scientists 58 D-Index: 166 scientists 59 D-Index: 144 scientists 60 D-Index: 152 scientists 61 D-Index: 141 scientists 62 D-Index: 138 scientists 63 D-Index: 131 scientists 64 D-Index: 118 scientists 65 D-Index: 114 scientists 66 D-Index: 119 scientists 67 D-Index: 95 scientists 68 D-Index: 87 scientists 69 D-Index: 77 scientists 70 D-Index: 89 scientists 71 D-Index: 69 scientists 72 D-Index: 54 scientists 73 D-Index: 46 scientists 74 D-Index: 55 scientists 75 D-Index: 54 scientists 76 D-Index: 49 scientists 77 D-Index: 53 scientists 78 D-Index: 46 scientists 79 D-Index: 28 scientists 80 D-Index: 39 scientists 81 D-Index: 36 scientists 82 D-Index: 24 scientists 83 D-Index: 26 scientists 84 D-Index: 36 scientists 85 D-Index: 18 scientists 86 D-Index: 25 scientists 87 D-Index: 19 scientists 88 D-Index: 26 scientists 89 D-Index: 27 scientists 90 D-Index: 23 scientists 91 D-Index: 15 scientists 92 D-Index: 12 scientists 93 D-Index: 9 scientists 94 D-Index: 15 scientists 95 D-Index: 10 scientists 96 D-Index: 13 scientists 97 D-Index: 13 scientists 98 D-Index: 9 scientists 99 D-Index: 7 scientists 100 D-Index: 7 scientists 101 D-Index: 8 scientists 102 D-Index: 7 scientists 103 D-Index: 7 scientists 104 D-Index: 9 scientists 105 D-Index: 6 scientists 106 D-Index: 9 scientists 107+ D-Index: 99 scientists
30 D-Index 107+

This scientist: 35 D-Index — 10th percentile

10% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 107 D-Index or more.

Overview

Xavier Descombes is affiliated with the French Institute for Research in Computer Science and Automation (INRIA) in France. Their research spans fields such as Medicine and Computer Science, with a particular focus on Artificial Intelligence, Radiology, Nuclear Medicine and Imaging, Oncology, Biophysics, and Molecular Biology.

Their work involves several main research topics including AI in cancer detection, Radiomics and Machine Learning in Medical Imaging, Cell Image Analysis Techniques, Colorectal Cancer Screening and Detection, Skin Protection and Aging, Neonatal skin health care, and Medical Image Segmentation Techniques.

Descombes has published in various venues, notably:

  • Journal of Biomedical Optics
  • bioRxiv (Cold Spring Harbor Laboratory)
  • Journal of Cell Science
  • Scientific Reports
  • International Journal of Biomedical Engineering and Technology

Some of their recent papers include:

  • Fibronectin Extra Domains tune cellular responses and confer topographically distinct features to fibril networks, 2021, Journal of Cell Science
  • Automating reflectance confocal microscopy image analysis for dermatological research: a review, 2022, Journal of Biomedical Optics
  • Multi-feature-based approach for white blood cells segmentation and classification in peripheral blood and bone marrow images, 2021, International Journal of Biomedical Engineering and Technology
  • Improving CNNs classification with pathologist-based expertise: the renal cell carcinoma case study, 2023, Scientific Reports
  • Biological Image Segmentation Using Region-Scalable Fitting Energy with B-Spline Level Set Implementation and Watershed, 2022, IRBM

Descombes frequently collaborates with a group of co-authors, including:

  • Damien Ambrosetti
  • Éric Debreuve
  • Francesco Ponzio
  • Imane Lboukili
  • Georgios N. Stamatas

Their research contributions show consistent interlinking of computer science techniques with medical and biological applications, particularly through the use of AI and machine learning methodologies in cancer detection and medical image processing. This multidisciplinary approach highlights their involvement in advancing imaging analysis and segmentation techniques, which are crucial for clinical diagnostics and biomedical research.

Best Publications

  • A Gibbs Point Process for Road Extraction from Remotely Sensed Images

    Radu Stoica;Xavier Descombes;Josiane Zerubia

  • Point processes for unsupervised line network extraction in remote sensing

    C. Lacoste;X. Descombes;J. Zerubia

  • Structural Approach for Building Reconstruction from a Single DSM

    F. Lafarge;X. Descombes;J. Zerubia;M. Pierrot-Deseilligny

  • Building Development Monitoring in Multitemporal Remotely Sensed Image Pairs with Stochastic Birth-Death Dynamics

    C. Benedek;X. Descombes;J. Zerubia

  • Estimation of Markov random field prior parameters using Markov chain Monte Carlo maximum likelihood

    X. Descombes;R.D. Morris;J. Zerubia;M. Berthod

  • Texture feature analysis using a gauss-Markov model in hyperspectral image classification

    G. Rellier;X. Descombes;F. Falzon;J. Zerubia

  • Comparison of six individual tree crown detection algorithms evaluated under varying forest conditions

    Morten Larsen;Mats Eriksson;Xavier Descombes;Guillaume Perrin

  • Automatic Building Extraction from DEMs using an Object Approach and Application to the 3D-city Modeling

    Florent Lafarge;Xavier Descombes;Josiane Zerubia;Marc Pierrot-Deseilligny

  • Building Outline Extraction from Digital Elevation Models Using Marked Point Processes

    Mathias Ortner;Xavier Descombes;Josiane Zerubia

  • Spatio-temporal fMRI analysis using Markov random fields

    X. Descombes;F. Kruggel;D.Y. Von Cramon

  • Object Extraction Using a Stochastic Birth-and-Death Dynamics in Continuum

    Xavier Descombes;Robert Minlos;Elena Zhizhina

  • Geometric Feature Extraction by a Multimarked Point Process

    F Lafarge;Georgy Gimel'farb;X Descombes

  • Coastline detection by a Markovian segmentation on SAR images

    Xavier Descombes;Miguel Moctezuma;Henri Maître;Jean-Paul Rudant

  • A Marked Point Process of Rectangles and Segments for Automatic Analysis of Digital Elevation Models

    M. Ortner;X. Descombes;J. Zerubia

  • Marked point process in image analysis

    X. Descombes;J. Zerubia

  • fMRI Signal Restoration Using a Spatio-Temporal Markov Random Field Preserving Transitions

    Xavier Descombes;Frithjof Kruggel;D.Yves von Cramon

  • Estimating Gaussian Markov random field parameters in a nonstationary framework: application to remote sensing imaging

    X. Descombes;M. Sigelle;F. Preteux

  • A marked point process model for tree crown extraction in plantations

    G. Perrin;X. Descombes;J. Zerubia

  • Texture Analysis through a Markovian Modelling and FuzzyClassification: Application to Urban Area Extraction fromSatellite Images

    A. Lorette;X. Descombes;J. Zerubia

  • Comparison of filtering methods for fMRI datasets.

    F. Kruggel;D.Y. von Cramon;X. Descombes

Frequent Co-Authors

Josiane Zerubia
Josiane Zerubia French Institute for Research in Computer Science and Automation - INRIA
Marc Pierrot-Deseilligny
Marc Pierrot-Deseilligny Gustave Eiffel University
Grégoire Malandain
Grégoire Malandain French Institute for Research in Computer Science and Automation - INRIA
D. Yves von Cramon
D. Yves von Cramon Max Planck Institute for Human Cognitive and Brain Sciences
Pierre Couteron
Pierre Couteron Institut de Recherche pour le Développement
Georgy Gimel'farb
Georgy Gimel'farb University of Auckland
Michèle Studer
Michèle Studer Université Côte d'Azur
Pierre Degond
Pierre Degond Toulouse Mathematics Institute
José Luiz Stape
José Luiz Stape North Carolina State University

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