Jakob Schwalb-Willmann just started his M.Sc. thesis titled “A deep learning movement prediction model using environmental data to identify movement anomalies”. He will combine animal movement and remote sensing data in order to develop a generic, data-driven DL-based model that predicts movements from movement history alongside environmental covariates in order to detect movement anomalies. He will establish simulated, controlled environments that allow precise adjustments of the model inputs to test the model’s feedbacks and its variability. It can be considered as a precursor study for the model’s deployment on real data and to only experimentally apply it on such due to the given constraints (time and content) of his M.Sc. thesis.
MainPro Project Meeting: Next Project Phase Launched
On Friday, November 21st, a MainPro project meeting was held to exchange ideas with our cooperating small and medium-sized enterprises (SMEs). Within our MainPro project, we aim to identify the changes caused by climate change in the Main Valley and its surroundings...
