World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
46
Citations
10061
World Ranking
6778
National Ranking
408

Toby P. Breckon 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 Toby P. Breckon 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: 233 publications — 57th percentile

57% of scientists in this discipline score the same or lower.

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

Toby P. Breckon 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 Toby P. Breckon 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: 46 D-Index — 53rd percentile

53% of scientists in this discipline score the same or lower.

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

Overview

Toby P. Breckon is affiliated with Durham University in the United Kingdom. Their research spans several areas within engineering and computer science, emphasizing computer vision, pattern recognition, and artificial intelligence.

Their scholarly output includes significant contributions to topics such as:

  • Advanced Neural Network Applications
  • Domain Adaptation and Few-Shot Learning
  • Advanced X-ray and CT Imaging
  • Remote Sensing and LiDAR Applications
  • Video Surveillance and Tracking Methods
  • Multimodal Machine Learning Applications
  • Medical Imaging Techniques and Applications

The primary fields of study for this researcher are Computer Science and Engineering, with 124 and 50 publications respectively. Their work further breaks down into subfields such as Computer Vision and Pattern Recognition, Artificial Intelligence, Radiology, Nuclear Medicine and Imaging, Biomedical Engineering, and Aerospace Engineering.

Recent notable papers include:

  • "Unsupervised Domain Adaptation via Structured Prediction Based Selective Pseudo-Labeling," 2020, published in Proceedings of the AAAI Conference on Artificial Intelligence
  • "Crowd Counting via Segmentation Guided Attention Networks and Curriculum Loss," 2022, published in IEEE Transactions on Intelligent Transportation Systems
  • "Adopting deep learning methods for airborne RGB fluvial scene classification," 2020, published in Remote Sensing of Environment
  • "Unmanned Aerial Vehicle Visual Detection and Tracking using Deep Neural Networks: A Performance Benchmark," 2021, published on arXiv (Cornell University)
  • "UNIT-DDPM: UNpaired Image Translation with Denoising Diffusion Probabilistic Models," 2021, published on arXiv (Cornell University)

Frequent co-authors in their publications include:

  • Neelanjan Bhowmik
  • Qian Wang
  • Yona Falinie A. Gaus
  • Brian K. S. Isaac-Medina
  • Hubert P. H. Shum

With a substantial number of publications appearing in venues such as arXiv (Cornell University), Pattern Recognition, the IEEE International Conference on Machine Learning and Applications, Neural Networks, and the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, their work is represented across major platforms in their fields.

Additionally, there is a book publication with IntechOpen titled "Technology, Science and Culture - A Global Vision, Volume IV" from 2023.

Best Publications

  • GANomaly : semi-supervised anomaly detection via adversarial training.

    Samet Akcay;Amir Atapour-Abarghouei;Toby P. Breckon

  • Fundamentals of Digital Image Processing: A Practical Approach with Examples in Matlab

    Chris Solomon;Toby Breckon

  • Skip-GANomaly: Skip Connected and Adversarially Trained Encoder-Decoder Anomaly Detection

    Samet Akcay;Amir Atapour-Abarghouei;Toby P. Breckon

  • Using Deep Convolutional Neural Network Architectures for Object Classification and Detection Within X-Ray Baggage Security Imagery

    Samet Akcay;Mikolaj E. Kundegorski;Chris G. Willcocks;Toby P. Breckon

  • Transfer learning using convolutional neural networks for object classification within X-ray baggage security imagery

    Samet Akcay;Mikolaj E. Kundegorski;Michael Devereux;Toby P. Breckon

  • Real-Time Monocular Depth Estimation Using Synthetic Data with Domain Adaptation via Image Style Transfer

    Amir Atapour-Abarghouei;Toby P. Breckon

  • Real-time people and vehicle detection from UAV imagery

    Anna Gaszczak;Toby P. Breckon;Jiwan Han

  • Unsupervised Domain Adaptation via Structured Prediction Based Selective Pseudo-Labeling

    Qian Wang;Toby P. Breckon

  • Dictionary of Computer Vision and Image Processing

    Robert B. Fisher;Toby P. Breckon;Kenneth Dawson-Howe;Andrew Fitzgibbon

  • Object Recognition using 3D SIFT in Complex CT Volumes.

    Gregory T. Flitton;Toby P. Breckon;Najla Megherbi Bouallagu

  • Improving feature-based object recognition for X-ray baggage security screening using primed visualwords

    Diana Turcsany;Andre Mouton;Toby P. Breckon

  • Towards automatic threat detection: A survey of advances of deep learning within X-ray security imaging

    Samet Akcay;Toby P. Breckon

  • A comparison of 3D interest point descriptors with application to airport baggage object detection in complex CT imagery

    Greg Flitton;Toby P. Breckon;Najla Megherbi

  • Experimentally Defined Convolutional Neural Network Architecture Variants for Non-Temporal Real-Time Fire Detection

    Andrew J. Dunnings;Toby P. Breckon

  • Style augmentation: data augmentation via style randomization

    Philip T. Jackson;Amir Atapour-Abarghouei;Stephen Bonner;Toby P. Breckon

  • Automatic Road Environment Classification

    I Tang;T P Breckon

  • Automatic real-time road marking recognition using a feature driven approach

    Alireza Kheyrollahi;Toby P. Breckon

  • Noise robust image edge detection based upon the automatic anisotropic Gaussian kernels.

    WeiChuan Zhang;WeiChuan Zhang;YaLi Zhao;Toby P. Breckon;Long Chen

  • Crowd Counting via Segmentation Guided Attention Networks and Curriculum Loss

    Qian Wang;Toby P. Breckon

  • Simulating Brain Signals: Creating Synthetic EEG Data via Neural-Based Generative Models for Improved SSVEP Classification

    Nik Khadijah Nik Aznan;Amir Atapour-Abarghouei;Stephen Bonner;Jason D. Connolly

  • Integrated speed limit detection and recognition from real-time video

    M.L. Eichner;T.P. Breckon

  • An experimental survey of metal artefact reduction in computed tomography.

    Andre Mouton;Najla Megherbi;Katrien Van Slambrouck;Johan Nuyts

Frequent Co-Authors

Robert B. Fisher
Robert B. Fisher University of Edinburgh
Emanuele Trucco
Emanuele Trucco University of Dundee
Horst Bischof
Horst Bischof Graz University of Technology
Changming Sun
Changming Sun Commonwealth Scientific and Industrial Research Organisation

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