Using machine learning to detect and predict changes of land use from aerial imagery


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Starting Date: earliest start: (2019-12-01) latest end: (2020-06-30)

Organization: Photogrammetry and Remote Sensing (Prof. Schindler)

Involved Host(s): Wegner Jan Dirk

Abstract: The ability to understand the evolution of land use (e.g. construction, change of land type) is crucial in fields such as urban planning, agriculture, natural resources management, and even autonomous flight. We will develop a Bayesian Recurrent Neural Network approach.

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Bayesian Deep Learning Recurrent Neural Networks Remote Sensing Agriculture Environmental Sciences Computer Vision


Labels: Master Thesis CLS Student Project (MPG ETH CLS)
Topics: Information, Computing and Communication Sciences Engineering and Technology