Lydia Gauerhof

15 papers A 1B 3C 1Journal 2Unranked 7

Year	Rank	Type	Title / Venue / Authors
2023	—	`—`	Essential properties for safe behaviour of a perception function in automated driving. Lydia Gauerhof
2022	C	`conf`	Automating Safety Argument Change Impact Analysis for Machine Learning Components. PRDC Carmen Cârlan, Lydia Gauerhof, Barbara Gallina, Simon Burton
2021	—	`conf`	On the Necessity of Explicit Artifact Links in Safety Assurance Cases for Machine Learning. ISSRE Workshops Lydia Gauerhof, Roman Gansch, Christian Heinzemann, Matthias Woehrle, Andreas Heyl
2021	J	`jnl`	Testing Deep Learning-based Visual Perception for Automated Driving. ACM Trans. Cyber Phys. Syst. Stephanie Abrecht, Lydia Gauerhof, Christoph Gladisch, Konrad Groh, Christian Heinzemann, Matthias Woehrle
2020	B	`conf`	Assuring the Safety of Machine Learning for Pedestrian Detection at Crossings. SAFECOMP Lydia Gauerhof, Richard Hawkins, Chiara Picardi, Colin Paterson, Yuki Hagiwara, Ibrahim Habli
2020	—	`conf`	Bayesian Model for Trustworthiness Analysis of Deep Learning Classifiers. AISafety@IJCAI Andrey Morozov, Emil Valiev, Michael Beyer, Kai Ding, Lydia Gauerhof, Christoph Schorn
2020	—	`conf`	Considering Reliability of Deep Learning Function to Boost Data Suitability and Anomaly Detection. ISSRE Workshops Lydia Gauerhof, Yuki Hagiwara, Christoph Schorn, Mario Trapp
2020	—	`conf`	FACER: A Universal Framework for Detecting Anomalous Operation of Deep Neural Networks. ITSC Christoph Schorn, Lydia Gauerhof
2020	J	`jnl`	Fault Injectors for TensorFlow: Evaluation of the Impact of Random Hardware Faults on Deep CNNs. CoRR Michael Beyer, Andrey Morozov, Emil Valiev, Christoph Schorn, Lydia Gauerhof, Kai Ding, Klaus Janschek
2020	A	`conf`	Reverse Variational Autoencoder for Visual Attribute Manipulation and Anomaly Detection. WACV Lydia Gauerhof, Nianlong Gu
2020	—	`conf`	Structuring the Safety Argumentation for Deep Neural Network Based Perception in Automotive Applications. SAFECOMP Workshops Gesina Schwalbe, Bernhard Knie, Timo Sämann, Timo Dobberphul, Lydia Gauerhof, Shervin Raafatnia, Vittorio Rocco
2019	—	`conf`	Confidence Arguments for Evidence of Performance in Machine Learning for Highly Automated Driving Functions. SAFECOMP Workshops Simon Burton, Lydia Gauerhof, Bibhuti Bhusan Sethy, Ibrahim Habli, Richard Hawkins
2018	B	`conf`	Structuring Validation Targets of a Machine Learning Function Applied to Automated Driving. SAFECOMP Lydia Gauerhof, Peter Munk, Simon Burton
2017	—	`conf`	Making the Case for Safety of Machine Learning in Highly Automated Driving. SAFECOMP Workshops Simon Burton, Lydia Gauerhof, Christian Heinzemann
2016	B	`conf`	Integration of a dynamic model in a driving simulator to meet requirements of various levels of automatization. Intelligent Vehicles Symposium Lydia Gauerhof, Anito Bilic, Christian Knies, Frank Diermeyer