Qualifications
- BSc
- MSc (University of Sunderland )
- MSc (University of Bradford)
- PhD (University of Lincoln)
Summary
Dr John Atanbori is a Computer Science Lecturer at the University of Hull. He completed his PhD in Computer Science from the University of Lincoln. His research focuses on the application of Computer Vision, Machine Learning, and Deep Learning to Plant Phenotyping, Agric-Tech and Animal Behaviour. Before his lecturing career, he worked in the computing industry, developing Computer Vision algorithms for Agricultural systems that use hyperspectral and depth cameras. He has also worked as a Research Fellow at the University of Nottingham’s Computer Vision Laboratory.
Journal Article
Convolutional Neural Net-Based Cassava Storage Root Counting Using Real and Synthetic Images
Atanbori, J., Montoya, M., Selvaraj, M. G., French, A. P., & Pridmore, T. P. (2019). Convolutional Neural Net-Based Cassava Storage Root Counting Using Real and Synthetic Images. Frontiers in Plant Science, 10, https://doi.org/10.3389/fpls.2019.01516
A low-cost aeroponic phenotyping system for storage root development: unravelling the below-ground secrets of cassava (Manihot esculenta)
Selvaraj, M. G., Montoya-P, M. E., Atanbori, J., French, A. P., & Pridmore, T. (2019). A low-cost aeroponic phenotyping system for storage root development: unravelling the below-ground secrets of cassava (Manihot esculenta). Plant Methods, 15(1), https://doi.org/10.1186/s13007-019-0517-6
Classification of bird species from video using appearance and motion features
Atanbori, J., Duan, W., Shaw, E., Appiah, K., & Dickinson, P. (2018). Classification of bird species from video using appearance and motion features. Ecological informatics, 48, 12-23. https://doi.org/10.1016/j.ecoinf.2018.07.005
Presentation / Conference
Towards Low-Cost Image-based Plant Phenotyping using Reduced-Parameter CNN.
Atanbori, J., Chen, F., French, A. P., & Pridmore, T. (2018, September). Towards Low-Cost Image-based Plant Phenotyping using Reduced-Parameter CNN. Paper presented at British Machine Vision Conference 2018, BMVC 2018, Northumbria University