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Departments >> Faculty of Engineering >> Department of Computer Science >> Chair of Computer Science 6 (Data Management) >>
E|ASY Opt (Compentence and Analytics Project for Data-driven Process and Production Optimization by Data Mining and Big Data)

REAPER: A Framework for Materializing and Reusing Deep-Learning Models

Within the framework of the EFRE-E/ASY-Opt subproject, the potential of data mining methods in the area of manufacturing is being investigated. Especially the training of Deep-Learning models is a computationally intensive task, which may take hours or several days. The training time can be shortened considerably by using an already trained model, as long as the goal and source task are closely related. This connection is not yet fully understood.
The aim of this research project is to implement a system called REAPER (Reusable Neural Network Pattern Repository) to support data scientists in storing and reusing already trained deep learning models.

Project manager:
Prof. i. R. Dr. Klaus Meyer-Wegener

Project participants:
Melanie Bianca Sigl, M. Sc., Luciano Melodia, M.A.

Keywords:
Production data management; predictive maintenance; data integration

Duration: 1.1.2017 - 31.12.2020

Sponsored by:
Europ. Fonds für Regionale Entwicklung (EFRE)

Mitwirkende Institutionen:
FAPS

Contact:
Sigl, Melanie Bianca
E-Mail: melanie.sigl@fau.de
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