World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
42
Citations
14105
World Ranking
8164
National Ranking
3498

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)
Nando de Freitas
Nando de Freitas DeepMind (United Kingdom)
Graham D. Finlayson
Graham D. Finlayson University of East Anglia
Emily A. Butler
Emily A. Butler University of Arizona
Barry M. Pryor
Barry M. Pryor University of Arizona
Deva Ramanan
Deva Ramanan Carnegie Mellon University
José L. Medina-Franco
José L. Medina-Franco National Autonomous University of Mexico

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