Martin Rogers
Researcher in Machine Learning
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Martin Rogers
Researcher in Machine Learning
Biography
I am a machine learning researcher in the Artificial Intelligence (AI) Lab at the British Antarctic Survey (BAS). My research primarily focusses on the application of machine learning techniques to detect features in satellite imagery, including multispectral visible and Synthetic Aperture Radar (SAR) datasets. I have previously trained and applied AI techniques, including convolutional neural networks, to automatically detect coastal features and land covers in satellite imagery. My current research focusses on the detection and classification of sea ice and other polar features in SAR imagery.
I am also the project manager for the AI4EO Guided Team Challenges, which forms part of the taught element of the Application of AI to the study of Environmental Risks (AI4ER) CDT.
Rogers, M. S. J., Bithell, M., Brooks, S. M and Spencer, T. 2021. VEdge_Detector: automated coastal vegetation edge detection using a convolutional neural network. International Journal of remote sensing. http://dx.doi.org/10.1080/01431161.2021.1897185
Arundell, K.L., Dubuffet, A., Wedell, N., Bojko, J., Rogers, M.S.J and Dunn, A.M., 2019. Podocotyle atomon (Trematoda: Digenea) impacts reproductive behaviour, survival and physiology in Gammarus zaddachi (Amphipoda). Diseases of aquatic organisms, 136(1), pp.51-62. https://doi.org/10.3354/dao03416
Rogers, M. 2016. Can Structure from Motion determine the efficacy of river re-meandering as a natural flood management measure? Available online: https://www.researchgate.net/profile/Martin_Rogers7
Publications from NERC Open Research Archive
2022
Bojko, Jamie, Reinke, Aaron W., Stentiford, Grant D., Williams, Bryony, Rogers, Martin S.J. ORCID record for Martin S.J. Rogers, Bass, David. (2022) Microsporidia: a new taxonomic, evolutionary, and ecological synthesis. Trends in Parasitology, 38. 642-659. 10.1016/j.pt.2022.05.007