Record link: 
http://hdl.handle.net/20.500.12708/209711
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Title: 
A Comparison of Monitoring Techniques for Deep Neural Networks
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Citation: 
Bartocci, E., & Essbai, W. (2024). A Comparison of Monitoring Techniques for Deep Neural Networks. In Bridging the Gap Between AI and Reality : Second International Conference, AISoLA 2024, Crete, Greece, October 30 – November 3, 2024, Proceedings. AISoLA 2024: International Conference on Bridging the Gap between AI and Reality, Kreta, Greece. https://doi.org/10.1007/978-3-031-75434-0_13
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Publisher DOI: 
10.1007/978-3-031-75434-0_13
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Publication Type: 
Inproceedings - Full-Paper Contribution
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Language: 
English
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Authors: 
Bartocci, Ezio 
Essbai, Wasim 
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Organisational Unit: 
E056-17 - Fachbereich Trustworthy Autonomous Cyber-Physical Systems 
E191-01 - Forschungsbereich Cyber-Physical Systems 
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Published in: 
Bridging the Gap Between AI and Reality : Second International Conference, AISoLA 2024, Crete, Greece, October 30 – November 3, 2024, Proceedings 
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ISBN: 
978-3-031-75433-3
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DOI of the book: 
10.1007/978-3-031-75434-0
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Date (published): 
30-Dec-2024
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Event name: 
AISoLA 2024: International Conference on Bridging the Gap between AI and Reality 
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Event date: 
30-Oct-2024 - 3-Nov-2024
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Event place: 
Kreta, Greece
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Peer reviewed: 
Yes
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Keywords: 
Deep neural networks; Anomaly Detection; Runtime monitoring
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Project title: 
Trustworthy Autonomous Cyber-Physical Systems: nicht bekannt (TTTech Auto AG; B & C Privatstiftung) 
Distribution Recovery for Invariant Generation of Probabilistic Programs: ICT19-018 (WWTF Wiener Wissenschafts-, Forschu und Technologiefonds) 
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Research Areas: 
Computer Engineering and Software-Intensive Systems: 100%
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Science Branch: 
1020 - Informatik: 100%
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Appears in Collections:
Conference Paper

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