Reducing the Burden of Aerial Image Labelling Through Human-in-the-Loop Machine Learning Methods
This dissertation presents an introduction to human-in-the-loop deep learning methods for remote sensing applications. It is motivated by the need to decrease the time spent by volunteers on semantic segmentation of remote sensing imagery. We look at two human-in-the-loop approaches of speeding up t...
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Format: | Dissertation |
Language: | English |
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Faculty of Engineering and the Built Environment
2021
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Online Access: | http://hdl.handle.net/11427/33908 |