We deploy machine learning algorithms to optimise data analyses in electron microscopy. Ongoing projects include:
- A model-independent zero loss peak (ZLP) subtraction in electron energy-loss spectroscopy (EELS) with neural networks;
- Automatising the classification and identification of relevant features in Hyperspectral EELS images;
- Deep learning classification of crystalline structures and defects from atomic resolution TEM images.
Meet the developers team: