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D-Index & Metrics

Computer Science

D-Index
41
Citations
7160
World Ranking
8838
National Ranking
349

Eric Granger 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 Eric Granger 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: 359 publications — 83rd percentile

83% of scientists in this discipline score the same or lower.

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

Eric Granger 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 Eric Granger 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: 41 D-Index — 40th percentile

40% of scientists in this discipline score the same or lower.

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

Overview

Eric Granger is affiliated with the École de Technologie Supérieure in Canada and is active in the field of Computer Science, with a focus on Computer Vision and Pattern Recognition. The scientist's work spans several subfields including Artificial Intelligence, Experimental and Cognitive Psychology, Signal Processing, and Radiology, Nuclear Medicine and Imaging.

Their key research topics include:

  • Advanced Neural Network Applications
  • Video Surveillance and Tracking Methods
  • Domain Adaptation and Few-Shot Learning
  • Emotion and Mood Recognition
  • Advanced Image and Video Retrieval Techniques
  • Face Recognition and Analysis
  • Human Pose and Action Recognition

Frequent coauthors in Eric Granger's research include:

  • Marco Pedersoli
  • Soufiane Belharbi
  • Ismail Ben Ayed
  • Pourya Shamsolmoali
  • Madhu Kiran

Eric Granger has published extensively, particularly in venues such as arXiv (Cornell University), Image and Vision Computing, and the IEEE Transactions on Affective Computing. Other publication outlets include the SSRN Electronic Journal and the 2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV).

Some recent papers authored or coauthored by Eric Granger are:

  • Boundary loss for highly unbalanced segmentation, 2020, Medical Image Analysis
  • MDN: A Deep Maximization-Differentiation Network for Spatio-Temporal Depression Detection, 2021, IEEE Transactions on Affective Computing
  • A Deep Multiscale Spatiotemporal Network for Assessing Depression From Facial Dynamics, 2020, IEEE Transactions on Affective Computing
  • A Joint Cross-Attention Model for Audio-Visual Fusion in Dimensional Emotion Recognition, 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
  • Deep Interpretable Classification and Weakly-Supervised Segmentation of Histology Images via Max-Min Uncertainty, 2021, IEEE Transactions on Medical Imaging

Additionally, Eric Granger has contributed to book publications with Springer Science+Business Media, including works titled Pattern Recognition and Artificial Intelligence published in 2022.

Best Publications

  • Multiple instance learning: A survey of problem characteristics and applications

    Marc-André Carbonneau;Veronika Cheplygina;Veronika Cheplygina;Eric Granger;Ghyslain Gagnon

  • Boundary loss for highly unbalanced segmentation.

    Hoel Kervadec;Jihene Bouchtiba;Christian Desrosiers;Eric Granger

  • Constrained-CNN losses for weakly supervised segmentation.

    Hoel Kervadec;Jose Dolz;Meng Tang;Eric Granger

  • Decoupling Direction and Norm for Efficient Gradient-Based L2 Adversarial Attacks and Defenses

    Jerome Rony;Luiz G. Hafemann;Luiz S. Oliveira;Ismail Ben Ayed

  • A what-and-where fusion neural network for recognition and tracking of multiple radar emitters

    Eric Granger;Mark A. Rubin;Mark A. Rubin;Stephen Grossberg;Pierre Lavoie

  • Pattern Recognition and Artificial Intelligence

    Unknown

  • Iterative Boolean combination of classifiers in the ROC space: An application to anomaly detection with HMMs

    Wael Khreich;Eric Granger;Ali Miri;Robert Sabourin

  • An adaptive classification system for video-based face recognition

    Jean-François Connolly;Eric Granger;Robert Sabourin

  • A survey of techniques for incremental learning of HMM parameters

    Wael Khreich;Eric Granger;Ali Miri;Robert Sabourin

  • Multi-feature extraction and selection in writer-independent off-line signature verification

    Dominique Rivard;Eric Granger;Robert Sabourin

  • Image synthesis with adversarial networks: A comprehensive survey and case studies

    Pourya Shamsolmoali;Pourya Shamsolmoali;Masoumeh Zareapoor;Eric Granger;Huiyu Zhou

  • MDN: A Deep Maximization-Differentiation Network for Spatio-Temporal Depression Detection

    Wheidima Carneirodemelo;Eric G. Granger;Miguel Bordallo Lopez

  • Dynamic selection of generative-discriminative ensembles for off-line signature verification

    Luana Batista;Eric Granger;Robert Sabourin

  • Hybrid writer-independent–writer-dependent offline signature verification system

    George S. Eskander;Robert Sabourin;Eric Granger

  • A Deep Multiscale Spatiotemporal Network for Assessing Depression from Facial Dynamics

    Wheidima Carneiro de Melo;Eric Granger;Abdenour Hadid

  • Unsupervised Domain Adaptation in the Dissimilarity Space for Person Re-identification

    Djebril Mekhazni;Amran Bhuiyan;George S. Eskander Ekladious;Eric Granger

  • A Joint Cross-Attention Model for Audio-Visual Fusion in Dimensional Emotion Recognition

    Unknown

  • A Unifying Mutual Information View of Metric Learning: Cross-Entropy vs. Pairwise Losses

    Malik Boudiaf;Jérôme Rony;Imtiaz Masud Ziko;Eric Granger

  • Pattern Recognition and Artificial Intelligence

    Unknown

  • Combining Global and Local Convolutional 3D Networks for Detecting Depression from Facial Expressions

    Wheidima Carneiro de Melo;Eric Granger;Abdenour Hadid

  • Depression Detection Based on Deep Distribution Learning

    Wheidima Carneiro de Melo;Eric Granger;Abdenour Hadid

  • Partially-supervised learning from facial trajectories for face recognition in video surveillance

    Miguel De-la-Torre;Eric Granger;Paulo V.W. Radtke;Robert Sabourin

  • The Tenth Visual Object Tracking VOT2022 Challenge Results

    Unknown

  • Cascaded Zoom-in Detector for High Resolution Aerial Images

    Unknown

  • Multiregion segmentation of bladder cancer structures in MRI with progressive dilated convolutional networks

    Jose Dolz;Xiaopan Xu;Jérôme Rony;Jing Yuan

  • Adaptive ROC-based ensembles of HMMs applied to anomaly detection

    Wael Khreich;Eric Granger;Ali Miri;Robert Sabourin

  • Bounding boxes for weakly supervised segmentation: Global constraints get close to full supervision

    Hoel Kervadec;Jose Dolz;Shanshan Wang;Eric Granger

  • Intravascular Imaging and Computer Assisted Stenting, and Large-Scale Annotation of Biomedical Data and Expert Label Synthesis

    M.J. Cardoso;T. Arbel;V. Cheplygina;S.-L. Lee

  • Multi-region segmentation of bladder cancer structures in MRI with progressive dilated convolutional networks

    Jose Dolz;Xiaopan Xu;Jerome Rony;Jing Yuan

Frequent Co-Authors

Robert Sabourin
Robert Sabourin École de Technologie Supérieure
Ismail Ben Ayed
Ismail Ben Ayed École de Technologie Supérieure
Jose Dolz
Jose Dolz École de Technologie Supérieure
Fabio Roli
Fabio Roli University of Genoa
Gian Luca Marcialis
Gian Luca Marcialis University of Cagliari
Ali Miri
Ali Miri Toronto Metropolitan University
Christian Desrosiers
Christian Desrosiers École de Technologie Supérieure
Abdenour Hadid
Abdenour Hadid University of Oulu
Stephen Grossberg
Stephen Grossberg Boston University
Giorgio Fumera
Giorgio Fumera University of Cagliari

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