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Lydia Gauerhof

Observed name: Gauerhof, Lydia
ORCID: 0000-0002-3504-0040
Observed ORCID: 0000-0002-3504-0040
OpenAlex ID: A5022623174
Making the Case for Safety of Machine Learning in Highly Automated Driving
2017 · Simon Burton, Lydia Gauerhof, et al. · Lecture notes in computer science · 139
Structuring Validation Targets of a Machine Learning Function Applied to Automated Driving
2018 · Lydia Gauerhof, Peter Munk, et al. · Lecture notes in computer science · 52
Assuring the Safety of Machine Learning for Pedestrian Detection at Crossings
2020 · Lydia Gauerhof, Richard Hawkins, et al. · Lecture notes in computer science · 42
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Confidence Arguments for Evidence of Performance in Machine Learning for Highly Automated Driving Functions
2019 · Simon Burton, Lydia Gauerhof, et al. · Lecture notes in computer science · 33
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Structuring the Safety Argumentation for Deep Neural Network Based Perception in Automotive Applications
2020 · Gesina Schwalbe, Bernhard Knie, et al. · Lecture notes in computer science · 27
Testing Deep Learning-based Visual Perception for Automated Driving
2021 · Stephanie Abrecht, Lydia Gauerhof, et al. · ACM Transactions on Cyber-Physical Systems · 22
FACER: A Universal Framework for Detecting Anomalous Operation of Deep Neural Networks
2020 · Christoph Schorn, Lydia Gauerhof · IEEE International Conference on Intelligent Transportation Systems (ITSC) · 17
Automating Safety Argument Change Impact Analysis for Machine Learning Components
2022 · Carmen Carlan, Lydia Gauerhof, et al. · IEEE Pacific Rim International Symposium on Dependable Computing (PRDC) · 14
Fault Injectors for TensorFlow: Evaluation of the Impact of Random Hardware Faults on Deep CNNs
2020 · Michael Beyer, Andrey Morozov, et al. · European Safety and Reliability Conference (ESREL) · 12
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Intelligent and Connected Cyber-Physical Systems: A Perspective from Connected Autonomous Vehicles
2020 · Wanli Chang, Simon Burton, et al. · Springer eBooks · 10
Reverse Variational Autoencoder for Visual Attribute Manipulation and Anomaly Detection
2020 · Lydia Gauerhof, Nianlong Gu · IEEE Winter Conference on Applications of Computer Vision · 7
Considering Reliability of Deep Learning Function to Boost Data Suitability and Anomaly Detection
2020 · Lydia Gauerhof, Yuki Hagiwara, et al. · IEEE International Symposium on Software Reliability Engineering Workshops (ISSREW) · 3
Integration of a dynamic model in a driving simulator to meet requirements of various levels of automatization
2016 · Lydia Gauerhof, Anito Bilic, et al. · IEEE Intelligent Vehicles Symposium · 3
On the Necessity of Explicit Artifact Links in Safety Assurance Cases for Machine Learning
2021 · Lydia Gauerhof, Roman Gansch, et al. · IEEE International Symposium on Software Reliability Engineering Workshops (ISSREW) · 1
Bayesian Model for Trustworthiness Analysis of Deep Learning Classifiers.
2020 · Andrey Morozov, Emil Valiev, et al. · International Joint Conference on Artificial Intelligence · 1
ADAS for the Communication between Automated and Manually Driven Cars
2015 · Lydia Gauerhof, Alexander Kürzl, et al. · mediaTUM – the media and publications repository of the Technical University Munich (Technical University Munich) · 1
Towards a Compositional Semantics for Quantitative Confidence Assessment in Assurance Arguments
2026 · Benjamin Herd, Jessica Kelly, et al. · European Dependable Computing Conference
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Works count: 19
Citation count: 384
H-index: 10
I10-index: 10
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