World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
42
Citations
14105
World Ranking
8163
National Ranking
3498

Kobus Barnard 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 Kobus Barnard 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: 121 publications — 15th percentile

15% of scientists in this discipline score the same or lower.

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

Kobus Barnard 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 Kobus Barnard 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: 42 D-Index — 43rd percentile

43% of scientists in this discipline score the same or lower.

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

Overview

Kobus Barnard is affiliated with the University of Arizona in the United States. Their research primarily lies within the field of Computer Science, with a focus on several subfields including Astronomy and Astrophysics, Artificial Intelligence, Computer Vision and Pattern Recognition, Atmospheric Science, and Plant Science.

Their recent publication record shows contributions to multiple domains, with research appearing in a variety of venues. Notable recent papers include:

  • NowCasting-Nets: Representation Learning to Mitigate Latency Gap of Satellite Precipitation Products Using Convolutional and Recurrent Neural Networks, 2022, published in IEEE Transactions on Geoscience and Remote Sensing
  • Asymmetric Contextual Modulation for Infrared Small Target Detection, 2020, published in arXiv (Cornell University)
  • MegaStitch: Robust Large-Scale Image Stitching, 2022, published in IEEE Transactions on Geoscience and Remote Sensing
  • Linking Extragalactic Transients and Their Host Galaxy Properties: Transient Sample, Multiwavelength Host Identification, and Database Construction, 2022, published in The Astrophysical Journal Supplement Series
  • Nowcasting-Nets: Deep Neural Network Structures for Precipitation Nowcasting Using IMERG, 2021, published in arXiv (Cornell University)

Frequent co-authors who have collaborated multiple times with Kobus Barnard include:

  • Ariyan Zarei
  • Yu-Jing Qin
  • Ann I. Zabludoff
  • Marina Kisley
  • Duke Pauli

They publish most often in the venues of arXiv (Cornell University) and IEEE Transactions on Geoscience and Remote Sensing, with additional publications in Zenodo (CERN European Organization for Nuclear Research), Computers and Electronics in Agriculture, and The Astrophysical Journal Supplement Series.

Key topics addressed in their research span several interdisciplinary areas, including:

  • Flood Risk Assessment and Management
  • Smart Agriculture and AI
  • Gamma-ray bursts and supernovae
  • Stellar, planetary, and galactic studies
  • Meteorological Phenomena and Simulations
  • Precipitation Measurement and Analysis
  • Advanced Image and Video Retrieval Techniques

Kobus Barnard's work reflects a strong emphasis on the integration of advanced computational methods, particularly neural networks and image processing techniques, applied across domains related to atmospheric science, astronomy, and agricultural systems.

Best Publications

  • Object Recognition as Machine Translation: Learning a Lexicon for a Fixed Image Vocabulary

    P. Duygulu;Kobus Barnard;J. F. G. de Freitas;David A. Forsyth

  • Matching words and pictures

    Kobus Barnard;Pinar Duygulu;David Forsyth;Nando de Freitas

  • Attentional Feature Fusion

    Yimian Dai;Fabian Gieseke;Stefan Oehmcke;Yiquan Wu

  • Learning the semantics of words and pictures

    K. Barnard;D. Forsyth

  • A comparison of computational color constancy algorithms. I: Methodology and experiments with synthesized data

    K. Barnard;V. Cardei;B. Funt

  • Asymmetric Contextual Modulation for Infrared Small Target Detection

    Yimian Dai;Yiquan Wu;Fei Zhou;Kobus Barnard

  • A comparison of computational color constancy Algorithms. II. Experiments with image data

    K. Barnard;L. Martin;A. Coath;B. Funt

  • A data set for color research

    Kobus Barnard;Lindsay Martin;Brian Funt;Adam Coath

  • Attentional Local Contrast Networks for Infrared Small Target Detection

    Yimian Dai;Yiquan Wu;Fei Zhou;Kobus Barnard

  • A Statistical Model for General Contextual Object Recognition

    Peter Carbonetto;Nando de Freitas;Kobus Barnard

  • Is Machine Colour Constancy Good Enough

    Brian V. Funt;Kobus Barnard;Lindsay Martin

  • Estimating the scene illumination chromaticity by using a neural network

    Vlad C. Cardei;Brian Funt;Kobus Barnard

  • Camera characterization for color research

    Kobus Barnard;Brian Funt

  • Clustering art

    K. Barnard;P. Duygulu;D. Forsyth

  • Color Constancy for Scenes with Varying Illumination

    Kobus Barnard;Graham Finlayson;Brian Funt

  • Learning Color Constancy

    Brian V. Funt;Vlad C. Cardei;Kobus Barnard

  • Color constancy under varying illumination

    G.D. Finlayson;B.V. Funt;K. Barnard

  • Bayesian geometric modeling of indoor scenes

    Luca Del Pero;Joshua Bowdish;Daniel Fried;Bonnie Kermgard

  • Word sense disambiguation with pictures

    Kobus Barnard;Matthew Johnson

  • Building models of animals from video

    D. Ramanan;D.A. Forsyth;K. Barnard

Frequent Co-Authors

Brian V. Funt
Brian V. Funt Simon Fraser University
Alon Efrat
Alon Efrat University of Arizona
David Forsyth
David Forsyth University of Illinois at Urbana-Champaign
Arnon Amir
Arnon Amir IBM (United States)
Keiji Yanai
Keiji Yanai University of Electro-Communications
Graham D. Finlayson
Graham D. Finlayson University of East Anglia
Nando de Freitas
Nando de Freitas DeepMind (United Kingdom)
Emily A. Butler
Emily A. Butler University of Arizona
Barry M. Pryor
Barry M. Pryor University of Arizona
José L. Medina-Franco
José L. Medina-Franco National Autonomous University of Mexico

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 also opens the door to diverse and flexible online programs that align with industry demand. Today’s students benefit from affordable, high-quality education without settling for traditional campus learning.

For those interested in big data, a data master online program offers focused training in analytics and data-driven decision-making. This can lead to opportunities in technology, finance, and health sectors.

If you seek leadership roles in the built environment, you might consider an accelerated construction management degree online. These programs are tailored for quick entry into managerial positions and are ideal for those aiming to advance rapidly.

Looking for broader business skills? Pursuing an mba online cheap lets you gain management expertise while keeping costs down.

Lastly, some students prefer to fast-track their career with efficient, advanced qualifications such as the best one year masters programs, combining speed and rigorous academics for greater impact in the job market.

Best Scientists Citing Kobus Barnard

Trending Scientists

Recently Published Articles