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Computer Science
Canada
2023

D-Index & Metrics

Computer Science

D-Index
55
Citations
135554
World Ranking
4168
National Ranking
161

David G. Lowe 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 G. Lowe 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: 117 publications — 14th percentile

14% of scientists in this discipline score the same or lower.

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

David G. Lowe 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 G. Lowe 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: 55 D-Index — 71st percentile

71% of scientists in this discipline score the same or lower.

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

Research.com Recognitions

  • 2023 - Research.com Computer Science in Canada Leader Award

Overview

David G. Lowe is affiliated with the University of British Columbia in Canada and focuses primarily on research within the social sciences. Their work spans several subfields, including sociology and political science, surgery, political science and international relations, molecular biology, and computer vision and pattern recognition.

The scientist's research topics include Australian history and society, paleontology and stratigraphy of fossils, colonial history and postcolonial studies, commonwealth politics including Australian politics and federalism, as well as technical subjects such as machine fault diagnosis techniques, fault detection and control systems, and engineering diagnostics and reliability.

Frequent publication venues for David G. Lowe are:

  • History Australia
  • Abstracts with programs - Geological Society of America
  • ISA Transactions
  • Scientific Reports
  • Finance and Economics Discussion Series

Recent scholarly articles authored or co-authored by David G. Lowe include:

  • Early and extremely early multi-label fault diagnosis in induction motors, 2020, ISA Transactions
  • Wireless monitoring and real-time adaptive predictive indicator of deterioration, 2020, Scientific Reports
  • Global Stablecoins: Monetary Policy Implementation Considerations from the U.S. Perspective, 2021, Finance and Economics Discussion Series
  • Can historians influence public policy? Challenges and possibilities, 2021, History Australia
  • New Zealand and the Colombo Plan in the long 1950s, 2020, History Australia

David G. Lowe has collaborated frequently with several co-authors, including:

  • Kate Darian-Smith
  • Carolyn Holbrook
  • Amit Sarwal
  • Mario Juez-Gil
  • Juan José Saucedo-Dorantes

The scientist has also contributed to book publications with notable publishers. Their works include:

  • Rising Power and Changing People: The Australian High Commission in India, published by ANU Press in 2022
  • The Australian Embassy in Tokyo and Australia-Japan Relations, published by ANU Press in 2022
  • The Colombo Plan, forthcoming in 2025 by Cambridge University Press

This profile reflects a multidisciplinary academic career intersecting social sciences with technical and historical research themes, emphasizing Australian history and political studies alongside engineering and molecular biology topics.

Best Publications

  • Distinctive Image Features from Scale-Invariant Keypoints

    David G. Lowe

  • Object recognition from local scale-invariant features

    D.G. Lowe

  • FAST APPROXIMATE NEAREST NEIGHBORS WITH AUTOMATIC ALGORITHM CONFIGURATION

    Marius Muja;David G. Lowe

  • Automatic Panoramic Image Stitching using Invariant Features

    Matthew Brown;David G. Lowe

  • Unsupervised Learning of Depth and Ego-Motion from Video

    Tinghui Zhou;Matthew Brown;Noah Snavely;David G. Lowe

  • Three-dimensional object recognition from single two-dimensional images

    D G Lowe

  • Perceptual Organization and Visual Recognition

    David G. Lowe

  • Scalable Nearest Neighbor Algorithms for High Dimensional Data

    Marius Muja;David G. Lowe

  • Shape indexing using approximate nearest-neighbour search in high-dimensional spaces

    J.S. Beis;D.G. Lowe

  • A Boosted Particle Filter: Multitarget Detection and Tracking

    Kenji Okuma;Ali Taleghani;Nando de Freitas;James J. Little

  • Fitting parameterized three-dimensional models to images

    D.G. Lowe

  • Invariant Features from Interest Point Groups

    Matthew Brown;David G. Lowe

  • Mobile Robot Localization and Mapping with Uncertainty using Scale-Invariant Visual Landmarks

    Stephen Se;David G. Lowe;James J. Little

  • Local feature view clustering for 3D object recognition

    D.G. Lowe

  • Vision-based mobile robot localization and mapping using scale-invariant features

    S. Se;D. Lowe;J. Little

  • Vision-based global localization and mapping for mobile robots

    S. Se;D.G. Lowe;J.J. Little

  • Method and apparatus for identifying scale invariant features in an image and use of same for locating an object in an image

    David G. Lowe

  • Multiclass Object Recognition with Sparse, Localized Features

    J. Mutch;D.G. Lowe

  • Robust Model-based Motion Tracking Through the Integration of Search and Estimation

    David G. Lowe

  • Low-Shot Learning with Imprinted Weights

    Hang Qi;Matthew Brown;David G. Lowe

  • Recognising Panoramas

    M. Brown;D. G. Lowe

Frequent Co-Authors

James J. Little
James J. Little University of British Columbia
Peter D. Lawrence
Peter D. Lawrence University of British Columbia
Septimiu E. Salcudean
Septimiu E. Salcudean University of British Columbia
Gustavo Carneiro
Gustavo Carneiro University of Surrey
Dinesh K. Pai
Dinesh K. Pai University of British Columbia
Robert Rohling
Robert Rohling University of British Columbia
Noah Snavely
Noah Snavely Cornell University
Kevin Lai
Kevin Lai Samsara
Michael C. Yip
Michael C. Yip University of California, San Diego
Radu Bogdan Rusu
Radu Bogdan Rusu Fyusion, Inc

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