Intelligent particle measurement technique (iPMT) (2021-2023)
The iPMT consortium consists of partners from industry and academia. The aim of the project is the development and validation of methods for the synthesis of training data for Deep Learning-based particle measurement techniques, exemplified by image-based methods for the detection of particles in (microscope ) images for the determination of particle size distribution, as well as time- and location-dependent measurements of the transmission spectra of particle dispersions with commercially available measurement devices as an example of multimodal sensor data. Complementary to this, methods for quantifying the quality of the generated synthetic data sets with respect to their suitability for machine learning will be developed and validated.
To facilitate future collaboration between research and industry with respect to classified particle images, methods for anonymization and abstraction of data sets from industry will be developed.
The project is funded by the German Federal Ministry of Education and Research (BMBF) and is a collaboration with Einar Kruis (Institut für Nanostrukturtechnik Universität Duisburg-Essen), Josef Pauli (Lehrstuhl für intelligente Systeme Universität Duisburg-Essen), Wolfgang Peukert (Lehrstuhl für Feststoff- und Grenzflächenverfahrenstechnik, FAU), Dietmar Lerche (LUM GmbH), Sebastian Maaß (SOPAT GmbH), Rainer Friehmelt (BASF SE, associated) and Lukas Pflug (CSC, FAU)
Runtime: 08/2021 – 07/2023, CSC: 100% E13
