Automated, adaptive and uncertainty-aware smart measurements using machine learning

Making multidimensional nanoscale measurements more efficient

Multidimensional measurements used for nanoscale material characterisation and defect identification are vital for advanced manufacturing and efficient quality control. Since these measurements are often slow or have limited resolution, faster and more efficient measurement strategies are needed.

Project develops novel and generalising approaches for smart multi-dimensional measurements with significantly reduced experimental
effort and with validated uncertainty evaluation.

VTT MIKES participates to the development of generic approaches for use of machine learning in metrology and specially to apply these methods in the hyperspectral imaging scatterometer application (HIS).


Call 2024: Metrology Support for Digital Transformation

The project (24DIT03) has received funding from the European Partnership on Metrology, co-financed from the European Union’s Horizon Europe Research and Innovation Programme and by the Participating States.