World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
46
Citations
10061
World Ranking
6777
National Ranking
410

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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