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Photo of Miss Jane Gallwey

Miss Jane Gallwey

Impact Fellow and Postgraduate

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Research topics:

Mining engineering, deep learning, LiDAR, satellite remote sensing, laser scanning, point cloud processing, image analysis, multispectral data.

Thesis:

Development of mining sector applications integrating emerging remote sensing and deep learning technologies

Supervisors:

Dr Matt Eyre and Professor John Coggan

Publications:

Gallwey, J., Robiati, C., Coggan, J., Vogt, D., Eyre, M., 2020. A Sentinel-2 based multispectral convolutional neural network for detecting artisanal small-scale mining in Ghana: Applying deep learning to shallow mining. Remote Sens. Environ. 248, 111970. https://doi.org/10.1016/j.rse.2020.111970

Gallwey, J., Yeomans, C., Tonkins, M., Coggan, J., Vogt, D., Eyre, M., 2020. Using Deep Learning and Hough Transformations to Infer Mineralised Veins from Lidar Data over Historic Mining Areas, in: Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci. ISPRS, Nice, France, pp. 1561–1568. https://doi.org/10.5194/isprs-archives-XLIII-B2-2020-1561-2020

Gallwey, J., Eyre, M., Tonkins, M., Coggan, J., 2019. Bringing Lunar LiDAR Back Down to Earth: Mapping Our Industrial Heritage Through Deep Transfer Learning. Remote Sens. 11, 1–22. https://doi.org/10.3390/rs11171994