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2020 – today
- 2024
[c7]Anita Graser, Axel Weissenfeld, Clemens Heistracher, Melitta Dragaschnig, Peter Widhalm:
Federated Learning for Anomaly Detection in Maritime Movement Data. MDM 2024: 77-82- 2023
- [c6]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:
MobiSpaces: An Architecture for Energy-Efficient Data Spaces for Mobility Data. IEEE Big Data 2023: 1487-1494 - [c5]Jana Kemnitz, Axel Weissenfeld, Leopold Schoeffl, Andreas Stiftinger, Daniel Rechberger, Bernhard Prangl, Thomas Kaufmann, Thomas Hiessl, Stephanie Holly, Clemens Heistracher, Daniel Schall:
An Edge Deployment Framework to Scale AI in Industrial Applications. ICFEC 2023: 24-32 - [c4]Clemens Heistracher, Pedro Casas, Stefan Stricker, Axel Weißenfeld, Daniel Schall, Jana Kemnitz:
Should I Sample it or Not? Improving Quality Assurance Efficiency Through Smart Active Sampling. IECON 2023: 1-6 - [i6]Viktorija Pruckovskaja, Axel Weissenfeld, Clemens Heistracher, Anita Graser, Julia Kafka, Peter Leputsch, Daniel Schall, Jana Kemnitz:
Federated Learning for Predictive Maintenance and Quality Inspection in Industrial Applications. CoRR abs/2304.11101 (2023) - [i5]Anahid N. Jalali, Anita Graser, Clemens Heistracher:
Towards eXplainable AI for Mobility Data Science. CoRR abs/2307.08461 (2023) - 2022
- [i4]Clemens Heistracher, Anahid N. Jalali, Jürgen Schneeweiss, Klaudia Kovacs, Catherine Laflamme, Bernhard Haslhofer:
Machine Learning Methods for Health-Index Prediction in Coating Chambers. CoRR abs/2205.15145 (2022) - [i3]Clemens Heistracher, Stefan Stricker, Pedro Casas, Daniel Schall, Jana Kemnitz:
Smart Active Sampling to enhance Quality Assurance Efficiency. CoRR abs/2209.11464 (2022) - 2021
- [c3]Clemens Heistracher, Anahid N. Jalali, Indu Strobl, Axel Suendermann, Sebastian Meixner, Stephanie Holly, Daniel Schall, Bernhard Haslhofer, Jana Kemnitz:
Transfer Learning Strategies for Anomaly Detection in IoT Vibration Data. IECON 2021: 1-6 - [i2]Clemens Heistracher, Anahid N. Jalali, Axel Suendermann, Sebastian Meixner, Daniel Schall, Bernhard Haslhofer, Jana Kemnitz:
Minimal-Configuration Anomaly Detection for IIoT Sensors. CoRR abs/2110.04049 (2021) - 2020
- [c2]Clemens Heistracher, Franck Mignet, Sven Schlarb:
Machine Learning Techniques for the Classification of Product Descriptions from Darknet Marketplaces. ICAI 2020: 128-137
2010 – 2019
- 2019
- [c1]Anahid N. Jalali, Clemens Heistracher, Alexander Schindler, Bernhard Haslhofer, Tanja Nemeth, Robert Glawar, Wilfried Sihn, Peter De Boer:
Predicting Time-to-Failure of Plasma Etching Equipment using Machine Learning. ICPHM 2019: 1-8 - [i1]Anahid N. Jalali, Clemens Heistracher, Alexander Schindler, Bernhard Haslhofer, Tanja Nemeth, Robert Glawar, Wilfried Sihn, Peter De Boer:
Predicting Time-to-Failure of Plasma Etching Equipment using Machine Learning. CoRR abs/1904.07686 (2019)
Coauthor Index
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