World's Best Scientists 2026 revealed!
Jean-François Aujol

Jean-François Aujol

D-Index & Metrics

Computer Science

D-Index
38
Citations
6207
World Ranking
10223
National Ranking
244

Jean-François Aujol 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 Jean-François Aujol 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: 152 publications — 28th percentile

28% of scientists in this discipline score the same or lower.

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

Jean-François Aujol 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 Jean-François Aujol 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: 38 D-Index — 30th percentile

30% of scientists in this discipline score the same or lower.

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

Overview

Jean-François Aujol is a researcher affiliated with the University of Bordeaux in France. Their work primarily spans the fields of computer science and engineering, with a particular emphasis on computer vision, pattern recognition, and computational mechanics.

Their research topics include:

  • Sparse and Compressive Sensing Techniques
  • Image and Signal Denoising Methods
  • Stochastic Gradient Optimization Techniques
  • Advanced Image Processing Techniques
  • Photoacoustic and Ultrasonic Imaging
  • Optimization and Variational Analysis
  • Advanced Optimization Algorithms Research

Among recent publications associated with or closely related to Jean-François Aujol's field of study are:

  • "Generative Adversarial Network for Pansharpening With Spectral and Spatial Discriminators," 2021, IEEE Transactions on Geoscience and Remote Sensing
  • "Projected Gradient Descent for Non-Convex Sparse Spike Estimation," 2020, IEEE Signal Processing Letters
  • "Convergence rates of an inertial gradient descent algorithm under growth and flatness conditions," 2020, Mathematical Programming
  • "Convergence Rates of the Heavy Ball Method for Quasi-strongly Convex Optimization," 2022, SIAM Journal on Optimization
  • "Convergence rates of the Heavy-Ball method under the Łojasiewicz property," 2022, Mathematical Programming

Frequent co-authors collaborating with Jean-François Aujol include:

  • Yann Traonmilin
  • Aude Rondepierre
  • Charles Dossal
  • Hippolyte Labarrière
  • Yannick Berthoumieu

Publications have often appeared in venues such as:

  • arXiv (Cornell University)
  • Mathematical Programming
  • IEEE Signal Processing Letters
  • SIAM Journal on Optimization
  • SIAM Journal on Imaging Sciences

Their research contributions show a significant focus on optimization methods, particularly involving gradient descent algorithms and heavy ball methods. These methods are explored both theoretically and in applied contexts related to imaging and signal processing. The range of topics also suggests an interdisciplinary approach blending mathematical programming with applications in engineering and computer vision.

Best Publications

  • Structure-Texture Image Decomposition--Modeling, Algorithms, and Parameter Selection

    Jean-François Aujol;Guy Gilboa;Tony Chan;Stanley Osher

  • A Variational Approach to Removing Multiplicative Noise

    Gilles Aubert;Jean-François Aujol

  • Image Decomposition into a Bounded Variation Component and an Oscillating Component

    Jean-François Aujol;Gilles Aubert;Laure Blanc-Féraud;Antonin Chambolle

  • Dual Norms and Image Decomposition Models

    Jean-François Aujol;Antonin Chambolle

  • Wavelet-based level set evolution for classification of textured images

    J.-F. Aujol;G. Aubert;L. Blanc-Feraud

  • Regularized Discrete Optimal Transport

    Sira Ferradans;Nicolas Papadakis;Gabriel Peyré;Jean-François Aujol

  • Some First-Order Algorithms for Total Variation Based Image Restoration

    Jean-François Aujol

  • Adaptive regularization of the NL-means: Application to image and video denoising

    Camille Sutour;Charles-Alban Deledalle;Jean-François Aujol

  • Modeling very oscillating signals. Application to image processing

    Gilles Aubert;Jean-Francois Aujol;Jean-Francois Aujol

  • Exemplar-Based Inpainting from a Variational Point of View

    Jean-François Aujol;Saïd Ladjal Ladjal;Simon Masnou

  • Normal Integration: A Survey

    Yvain Quéau;Jean-Denis Durou;Jean-François Aujol

  • Color image decomposition and restoration

    Jean-François Aujol;Sung Ha Kang

  • The TVL1 Model: A Geometric Point of View

    Vincent Duval;Jean-François Aujol;Yann Gousseau

  • A Bias-Variance Approach for the Nonlocal Means

    Vincent Duval;Jean-François Aujol;Yann Gousseau

  • Stability of over-relaxations for the Forward-Backward algorithm, application to FISTA

    Jean-François Aujol;Charles Dossal

  • Scale Recognition, Regularization Parameter Selection, and Meyer's G Norm in Total Variation Regularization

    David M. Strong;Jean Francois Aujol;Tony F. Chan

  • Image decomposition application to SAR images

    Jean-François Aujol;Gilles Aubert;Laure Blanc-Féraud;Antonin Chambolle

  • Constrained and SNR-Based Solutions for TV-Hilbert Space Image Denoising

    Jean-François Aujol;Guy Gilboa

  • Regularized Discrete Optimal Transport

    Sira Ferradans;Nicolas Papadakis;Julien Rabin;Gabriel Peyré

  • Integrating the Normal Field of a Surface in the Presence of Discontinuities

    Jean-Denis Durou;Jean-François Aujol;Frédéric Courteille

  • Scale Space and Variational Methods in Computer Vision

    Jean-François Aujol;Mila Nikolova;Nicolas Papadakis

  • The TVL1 model : a geometric point of view Une étude géométrique du modèle TVL1

    Vincent Duval;Jean-François Aujol;Yann Gousseau

Frequent Co-Authors

Yann Gousseau
Yann Gousseau Télécom ParisTech
Gabriel Peyré
Gabriel Peyré École Normale Supérieure
Gilles Aubert
Gilles Aubert Université Côte d'Azur
Bin Luo
Bin Luo Anhui University
Gabriele Steidl
Gabriele Steidl Technical University of Berlin
Tony F. Chan
Tony F. Chan University of California, Los Angeles
Antonin Chambolle
Antonin Chambolle Paris Dauphine University
Gui-Song Xia
Gui-Song Xia Wuhan University
Vicent Caselles
Vicent Caselles University of Valencia
Vincent Lepetit
Vincent Lepetit École des Ponts ParisTech

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