Clemens Heistracher

According to our database, Clemens Heistracher authored at least 11 papers between 2019 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Towards eXplainable AI for Mobility Data Science.

Anahid N. Jalali, Anita Graser, Clemens Heistracher

CoRR, 2023

Federated Learning for Predictive Maintenance and Quality Inspection in Industrial Applications.

Viktorija Pruckovskaja, Axel Weissenfeld, Clemens Heistracher, Anita Graser, Julia Kafka, Peter Leputsch, Daniel Schall, Jana Kemnitz

CoRR, 2023

Should I Sample it or Not? Improving Quality Assurance Efficiency Through Smart Active Sampling.

Clemens Heistracher, Pedro Casas, Stefan Stricker, Axel Weißenfeld, Daniel Schall, Jana Kemnitz

Proceedings of the 49th Annual Conference of the IEEE Industrial Electronics Society, 2023

An Edge Deployment Framework to Scale AI in Industrial Applications.

Jana Kemnitz, Axel Weissenfeld, Leopold Schoeffl, Andreas Stiftinger, Daniel Rechberger, Bernhard Prangl, Thomas Kaufmann, Thomas Hiessl, Stephanie Holly, Clemens Heistracher, Daniel Schall

Proceedings of the 7th IEEE International Conference on Fog and Edge Computing, 2023

MobiSpaces: An Architecture for Energy-Efficient Data Spaces for Mobility Data.

Christos Doulkeridis, Georgios M. Santipantakis, Nikolaos Koutroumanis, George Makridis, Vasilis Koukos, George S. Theodoropoulos, Yannis Theodoridis, Dimosthenis Kyriazis, Pavlos Kranas, Diego Burgos, Ricardo Jiménez-Peris, Mariana M. G. Duarte, Mahmoud Attia Sakr, Esteban Zimányi, Anita Graser, Clemens Heistracher, Kristian Torp, Ioannis Chrysakis, Theofanis Orphanoudakis, Evgenia Kapassa, Marios Touloupou, Jürgen Neises, Petros Petrou, Sophia Karagiorgou, Rosario Catelli, Domenico Messina, Marcelo Corrales Compagnucci, Matteo Falsetta

Proceedings of the IEEE International Conference on Big Data, 2023

2022

Smart Active Sampling to enhance Quality Assurance Efficiency.

Clemens Heistracher, Stefan Stricker, Pedro Casas, Daniel Schall, Jana Kemnitz

CoRR, 2022

Machine Learning Methods for Health-Index Prediction in Coating Chambers.

Clemens Heistracher, Anahid N. Jalali, Jürgen Schneeweiss, Klaudia Kovacs, Catherine Laflamme, Bernhard Haslhofer

CoRR, 2022

2021

Minimal-Configuration Anomaly Detection for IIoT Sensors.

Clemens Heistracher, Anahid N. Jalali, Axel Suendermann, Sebastian Meixner, Daniel Schall, Bernhard Haslhofer, Jana Kemnitz

CoRR, 2021

Transfer Learning Strategies for Anomaly Detection in IoT Vibration Data.

Clemens Heistracher, Anahid N. Jalali, Indu Strobl, Axel Suendermann, Sebastian Meixner, Stephanie Holly, Daniel Schall, Bernhard Haslhofer, Jana Kemnitz

Proceedings of the IECON 2021, 2021

2020

Machine Learning Techniques for the Classification of Product Descriptions from Darknet Marketplaces.

Clemens Heistracher, Franck Mignet, Sven Schlarb

Proceedings of the 11th International Conference on Applied Informatics (ICAI 2020), 2020

2019

Predicting Time-to-Failure of Plasma Etching Equipment using Machine Learning.

Anahid N. Jalali, Clemens Heistracher, Alexander Schindler, Bernhard Haslhofer, Tanja Nemeth, Robert Glawar, Wilfried Sihn, Peter De Boer

Proceedings of the 2019 IEEE International Conference on Prognostics and Health Management, 2019