Speaker
Tobias Habermann
(Fulda University of Applied Sciences)
Description
An exploration into the application of machine learning (ML) approaches to identify pile-ups and correct them in single particle counters at the GSI Helmholtz Centre for Heavy Ion Research in presented.
About 100000 particle pulse data from various spills were manually labelled and a convolutional neural network (CNN) was developed to accurately count the number of particles without domain-specific knowledge.
This contribution represents proof-of-work for a fast error free automated particle counting system. The identified algorithm was developed with a perspective of implementation into an FPGA.
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Author
Tobias Habermann
(Fulda University of Applied Sciences)
Co-authors
Martin Kumm
(Fulda University of Applied Sciences)
Plamen Boutachkov
(GSI Helmholtz Centre for Heavy Ion Research)
Rahul Singh
(GSI Helmholtz Centre for Heavy Ion Research)
