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.
Successful fieldwork at the Naryn River in Kyrgyzstan
During the last week, EORC PI Florian Betz, EAGLE student Ariana Arguello-Cordero and FluBig team member Magdalena Lauermann from Catholic University Eichstätt-Ingolstadt have been on a field campaign in Kyrgyzstan to collect data for the FluBig project dedicated to...
