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.
EORC at the joint NSO-GfÖ 2026 conference in Odense, Denmark
This week, the EORC is participating in the joint NSO-GfÖ 2026 conference in Odense, Denmark. The conference brings together researchers of all career stages from all across ecology research, representing a wide range of methods and applications, including topics at...
