World's Best Scientists 2026 revealed!
David A. Clausi

David A. Clausi

D-Index & Metrics

Computer Science

D-Index
48
Citations
11890
World Ranking
6093
National Ranking
234

David A. Clausi 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 David A. Clausi 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: 331 publications — 79th percentile

79% of scientists in this discipline score the same or lower.

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

David A. Clausi 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 David A. Clausi 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: 48 D-Index — 58th percentile

58% of scientists in this discipline score the same or lower.

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

Overview

David A. Clausi is affiliated with the University of Waterloo in Canada. Their research spans several fields including Earth and Planetary Sciences, Computer Science, and Engineering. Within these domains, their work covers notable subfields such as Atmospheric Science, Computer Vision and Pattern Recognition, Economics and Econometrics, Artificial Intelligence, and Environmental Chemistry.

The scientist's research topics include Arctic and Antarctic ice dynamics, Video Analysis and Summarization, Sports Analytics and Performance, Methane Hydrates and Related Phenomena, Cryospheric studies and observations, Anomaly Detection Techniques and Applications, and Underwater Acoustics Research.

David A. Clausi has contributed numerous papers in prominent publication venues. Their frequent publication venues include:

  • arXiv (Cornell University)
  • IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
  • IEEE Transactions on Geoscience and Remote Sensing
  • Remote Sensing
  • IEEE Geoscience and Remote Sensing Letters

Among their recent papers are:

  • "Lake Ice-Water Classification of RADARSAT-2 Images by Integrating IRGS Segmentation with Pixel-Based Random Forest Labeling", 2020, in Remote Sensing
  • "Sea Ice Concentration Estimation: Using Passive Microwave and SAR Data With a U-Net and Curriculum Learning", 2021, in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
  • "Player tracking and identification in ice hockey", 2022, in Expert Systems with Applications
  • "Evaluation of a Neural Network With Uncertainty for Detection of Ice and Water in SAR Imagery", 2020, in IEEE Transactions on Geoscience and Remote Sensing
  • "Sea-Ice Mapping of RADARSAT-2 Imagery by Integrating Spatial Contexture With Textural Features", 2022, in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing

Frequent collaborators in their research include Linlin Xu, Yuhao Chen, John Zelek, Alexander Wong, and K. Andrea Scott. These collaborations have resulted in numerous joint publications.

Best Publications

  • An analysis of co-occurrence texture statistics as a function of grey level quantization

    David A Clausi

  • Designing Gabor filters for optimal texture separability

    David A. Clausi;M. Ed Jernigan

  • Lung Nodule Classification Using Deep Features in CT Images

    Devinder Kumar;Alexander Wong;David A. Clausi

  • ARRSI: Automatic Registration of Remote-Sensing Images

    A. Wong;D.A. Clausi

  • Design-based texture feature fusion using Gabor filters and co-occurrence probabilities

    D.A. Clausi;Huang Deng

  • Unsupervised image segmentation using a simple MRF model with a new implementation scheme

    Huawu Deng;David A. Clausi

  • IRGS: Image Segmentation Using Edge Penalties and Region Growing

    Qiyao Yu;D.A. Clausi

  • Unsupervised segmentation of synthetic aperture Radar sea ice imagery using a novel Markov random field model

    Huawu Deng;D.A. Clausi

  • Comparing cooccurrence probabilities and Markov random fields for texture analysis of SAR sea ice imagery

    D.A. Clausi;Bing Yue

  • Intra-retinal layer segmentation in optical coherence tomography images

    Akshaya Mishra;Alexander Wong;Kostadinka Bizheva;David A. Clausi

  • Unsupervised Polarimetric SAR Image Segmentation and Classification Using Region Growing With Edge Penalty

    P. Yu;A. K. Qin;D. A. Clausi

  • Comparison and fusion of co‐occurrence, Gabor and MRF texture features for classification of SAR sea‐ice imagery

    David A. Clausi

  • Sea Ice Concentration Estimation During Melt From Dual-Pol SAR Scenes Using Deep Convolutional Neural Networks: A Case Study

    Lei Wang;K. Andrea Scott;Linlin Xu;David A. Clausi

  • Gaussian MRF rotation-invariant features for image classification

    Huawu Deng;D.A. Clausi

  • General Bayesian estimation for speckle noise reduction in optical coherence tomography retinal imagery

    Alexander Wong;Akshaya Mishra;Kostadinka Bizheva;David A Clausi

  • Unsupervised image segmentation using a simple MRF model with a new implementation scheme

    Huawu Deng;D.A. Clausi

  • Using the Canny edge detector for feature extraction and enhancement of remote sensing images

    M. Ali;D. Clausi

  • Automated Ice–Water Classification Using Dual Polarization SAR Satellite Imagery

    Steven Leigh;Zhijie Wang;David A. Clausi

  • Segmentation of Skin Lesions From Digital Images Using Joint Statistical Texture Distinctiveness

    Jeffrey Glaister;Alexander Wong;David A. Clausi

  • A fast method to determine co-occurrence texture features

    D.A. Clausi;M.E. Jernigan

Frequent Co-Authors

Alexander Wong
Alexander Wong University of Waterloo
Paul Fieguth
Paul Fieguth University of Waterloo
A. K. Qin
A. K. Qin Swinburne University of Technology
Richard L. Hughson
Richard L. Hughson University of Waterloo
Steven L. Waslander
Steven L. Waslander University of Toronto
Samarjit Chakraborty
Samarjit Chakraborty University of North Carolina at Chapel Hill
Lars Kaleschke
Lars Kaleschke Alfred Wegener Institute for Polar and Marine Research
Andrew K. C. Wong
Andrew K. C. Wong University of Waterloo
Gangyao Kuang
Gangyao Kuang National University of Defense Technology

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