World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
62
Citations
23538
World Ranking
2837
National Ranking
164

Richard Bowden 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 Richard Bowden 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: 296 publications — 73rd percentile

73% of scientists in this discipline score the same or lower.

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

Richard Bowden 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 Richard Bowden 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: 62 D-Index — 80th percentile

80% 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

  • 2016 - Fellow of the International Association for Pattern Recognition (IAPR) For contributions to computer vision in the fields of sign language, gesture and activity recognition and service to IAPR

Overview

Richard Bowden is affiliated with the University of Surrey in the United Kingdom and specializes in computer science with a strong focus on computer vision and pattern recognition. Their work encompasses a variety of subfields including human-computer interaction, developmental and educational psychology, artificial intelligence, and control and systems engineering.

Their research mainly addresses topics related to hand gesture recognition systems, human pose and action recognition, and hearing impairment and communication. Other areas of their expertise include advanced vision and imaging, multimodal machine learning applications, robotics and sensor-based localization, and autonomous vehicle technology and safety.

Recent publications by Richard Bowden include:

  • Text2Sign: Towards Sign Language Production Using Neural Machine Translation and Generative Adversarial Networks, 2020, International Journal of Computer Vision
  • D'ya Like DAGs? A Survey on Structure Learning and Causal Discovery, 2022, ACM Computing Surveys
  • Translating Images into Maps, 2022, 2022 International Conference on Robotics and Automation (ICRA)
  • Continuous 3D Multi-Channel Sign Language Production via Progressive Transformers and Mixture Density Networks, 2021, International Journal of Computer Vision
  • A Survey of Deep Learning Applications to Autonomous Vehicle Control, 2020, IEEE Transactions on Intelligent Transportation Systems

Frequent coauthors include:

  • Necati Cihan Camgöz
  • Oscar Méndez
  • Ben Saunders
  • Simon Hadfield
  • Chris Russell

Richard Bowden has contributed extensively to venues such as arXiv (Cornell University), with 64 publications, as well as the 2021 16th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2021), Zurich Open Repository and Archive (University of Zurich), 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), and International Journal of Computer Vision.

In recognition of their work, Richard Bowden was awarded the status of Fellow of the International Association for Pattern Recognition (IAPR) in 2016 for contributions to computer vision in sign language, gesture and activity recognition, and service to IAPR.

Best Publications

  • An Improved Adaptive Background Mixture Model for Real-time Tracking with Shadow Detection

    P. KaewTraKulPong;P. KaewTraKulPong;R. Bowden

  • The Visual Object Tracking VOT2016 Challenge Results

    Matej Kristan;Aleš Leonardis;Jiři Matas;Michael Felsberg

  • The Visual Object Tracking VOT2017 Challenge Results

    Matej Kristan;Ales Leonardis;Jiri Matas;Michael Felsberg

  • The Visual Object Tracking VOT2015 Challenge Results

    Matej Kristan;Jiri Matas;Ale Leonardis;Michael Felsberg

  • The Visual Object Tracking VOT2013 Challenge Results

    Matej Kristan;Roman Pflugfelder;Ale Leonardis;Jiri Matas

  • A Survey of Deep Learning Applications to Autonomous Vehicle Control

    Sampo Kuutti;Richard Bowden;Yaochu Jin;Phil Barber

  • The sixth visual object tracking VOT2018 challenge results

    Matej Kristan;Aleš Leonardis;Jiří Matas;Michael Felsberg

  • Neural Sign Language Translation

    Necati Cihan Camgoz;Simon Hadfield;Oscar Koller;Hermann Ney

  • Sign Language Transformers: Joint End-to-End Sign Language Recognition and Translation

    Necati Cihan Camgoz;Oscar Koller;Simon Hadfield;Richard Bowden

  • Spelling it out: Real-time ASL fingerspelling recognition

    Nicolas Pugeault;Richard Bowden

  • Local binary patterns for multi-view facial expression recognition

    S. Moore;R. Bowden

  • The Visual Object Tracking VOT2014 challenge results

    Matej Kristan;Roman P. Pflugfelder;Ales Leonardis;Jiri Matas

  • SubUNets: End-to-End Hand Shape and Continuous Sign Language Recognition

    Necati Cihan Camgoz;Simon Hadfield;Oscar Koller;Richard Bowden

  • A boosted classifier tree for hand shape detection

    Eng-Jon Ong;R. Bowden

  • Deep Hand: How to Train a CNN on 1 Million Hand Images When Your Data is Continuous and Weakly Labelled

    Oscar Koller;Hermann Ney;Richard Bowden

  • Weakly Supervised Learning with Multi-Stream CNN-LSTM-HMMs to Discover Sequential Parallelism in Sign Language Videos

    Oscar Koller;Necati Cihan Camgoz;Hermann Ney;Richard Bowden

  • Sign Language Recognition

    Helen Cooper;Brian Holt;Richard Bowden

  • Deep Sign: Hybrid CNN-HMM for Continuous Sign Language Recognition

    Oscar Tobias Anatol Koller;Sepehr Zargaran;Hermann Ney;Richard Bowden

  • Text2Sign: Towards Sign Language Production Using Neural Machine Translation and Generative Adversarial Networks.

    Stephanie Stoll;Necati Cihan Camgoz;Simon Hadfield;Richard Bowden

  • A Linguistic Feature Vector for the Visual Interpretation of Sign Language

    Richard Bowden;Richard Bowden;David Windridge;Timor Kadir;Andrew Zisserman

  • Action Recognition Using Mined Hierarchical Compound Features

    A Gilbert;J Illingworth;R Bowden

Frequent Co-Authors

Hermann Ney
Hermann Ney RWTH Aachen University
Jiri Matas
Jiri Matas Czech Technical University in Prague
John Illingworth
John Illingworth University of Surrey
Michael Felsberg
Michael Felsberg Linköping University
Matej Kristan
Matej Kristan University of Ljubljana
Qingming Huang
Qingming Huang University of Chinese Academy of Sciences
Fahad Shahbaz Khan
Fahad Shahbaz Khan Mohamed bin Zayed University of Artificial Intelligence
Ales Leonardis
Ales Leonardis University of Birmingham
Philip H. S. Torr
Philip H. S. Torr University of Oxford

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

Exploring a computer science degree in the USA opens up a variety of career pathways—not just in tech companies, but also in fields like finance, healthcare, and engineering. With the flexibility of online learning, more students are choosing computer science degree online programs to gain essential technical skills without relocating or pausing their careers.

Online degrees aren’t limited to computer science. For those interested in sustainability and the environment, affordable programs such as the cheapest online environmental science degree or cheapest online master's mechanical engineering offer a budget-friendly path to impactful professions. Graduates can explore what jobs can you get with an environmental science degree, ranging from research roles to consulting and policy work.

As online degrees continue to gain recognition, they provide greater flexibility without compromising on career outcomes—helping students build valuable, industry-relevant expertise at their own pace and budget.

Best Scientists Citing Richard Bowden

Trending Scientists

Recently Published Articles