Deployment of a multi-classifier approach to improve land cover classification accuracy

multi_classifierThis study will examine whether the application of hybrid classifiers increases the classification accuracy in comparison to a single classifier. A combination between parametric and non-parametric classifiers will be applied and their performance will be assessed. The student is expected to gain a deep knowledge of applied Machine Learning algorithms within this innovation laboratory.

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[spotlight] Lecturer Spotlight: Martin Wegmann

[spotlight] Lecturer Spotlight: Martin Wegmann

If you've ever sat in a Würzburg classroom learning how to wrangle satellite data, there's a good chance Martin Wegmann was the one standing at the front. He's been the driving force behind the EAGLE MSc program, the Applied Earth Observation degree at the University...

EAGLE Internship Presentation: Svalbard

EAGLE Internship Presentation: Svalbard

On July 07, 2026, Aoibhin Murphy and Marlene Sehrbrock will present her internship results on " Svalbard" at 12:00 in seminar room 3, John-Skilton-Str. 4a. From the abstract: Using thermal and RGB imagery collected via UAVs, we investigated the potential of thermal...

EireR R package: unified gateway to Irish geospatial data

EireR R package: unified gateway to Irish geospatial data

Anyone who's tried to do geospatial work across the whole island of Ireland knows the headache. Ireland is one island geographically, but it's split across two jurisdictions, the Republic and Northern Ireland, and each one runs its own data infrastructure. Different...

Impact of agrophotovoltaic facilities – an R package

Impact of agrophotovoltaic facilities – an R package

There's a new R package on the block, and it's solving a problem that sounds simple until you actually try to do it: how do you tell whether putting solar panels over a farm field is good or bad for the soil and the crops around them? Marlene, one of our EAGLE...