About the Project
sensed data, such as multispectral/hyperspectral images, as well as LIDAR data, which provide height information of terrain. Data sources range from UAV captured data, airborne data, to satellite data. Methodology and algorithms will be developed to classify terrain features in these data, based on advanced techniques of computer vision, image processing, statistical pattern
classification, and machine learning. The application of the research covers land-cover change detection, crop growth monitoring, and may extend to environmental monitoring.
First degree in computer science, physics, engineering, and mathematics with 2:1 or abov. MSc degree in the relevant subject areas is desired.
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