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Applying machine learning to ecotoxicology could help reduce the number of animal tests, costs, and animals sacrificed while preserving the accuracy of the in vivo tests.

Food insecurity in sub-Saharan Africa is widespread, with crop yields much lower than in many developed regions. The project aims to use laser spectroscopy to measure fluxes and isotopic composition of N2O from maize and potato crops subjected to a range of fertilization levels.

It is difficult to effectively monitor and track progress in urban housing. We attempt to overcome these limitations by utilizing self-supervised learning with over 15 million street-level images taken between 2008 and 2021 to measure change in London.

As we endeavor to reduce global CO2 emissions to avoid the worst impacts of climate change, Bühler Group is laying the technical foundations to make real impacts on the industry’s emissions through an innovative approach to optimizing manufacturing operations.

Optoacoustic imaging is a new, real-time feedback and non-invasive imaging tool with increasing application in clinical and pre-clinical settings. The DLBIRHOUI project tackles some of the major challenges in optoacoustic imaging to facilitate faster adoption of this technology for clinical use.

LeafSim is an example-based explainable AI (XAI) technique for decision tree-based ensemble methods, explaining model predictions by identifying training data points that most influence a given prediction.