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Lukas Hacker

Affiliation

RD ADAS Software Platform

Mercedes-Benz AG

Sindelfingen, Germany

Publication Topics

Adversarial Attacks,
Adversary Model,
Automated Vehicles,
Deep Learning,
Deep Neural Network,
Deep Neural Network Model,
Detection Methods,
Detection Performance,
Different Types Of Errors,
Distribution Of Training Data,
Error Detection,
Fast Gradient Sign Method

Biography

Lukas Hacker received the B.Sc. and M.Sc. degrees from the Technical University of Kaiserslautern in 2017 and 2020, respectively. During the bachelor and master thesis with the Research Departments of Opel Automobile GmbH, Rüsselsheim and Mercedes Benz AG, Sindelfingen, he specialized in control theory and artificial intelligence. Since 2020, he takes part in a Ph.D. (Dr.-Ing.) Program with Mercedes-Benz AG, Sindelfingen, in cooperation with the Institute of Measurement and Sensor Technology, Technical University of Kaiserslautern. His research focuses on SOTIF and safe AI in the context of automated driving. For his research activities, he received the Ferchau Young Talents Award in 2017. Furthermore, he is a member of the DIN Mirror Commi...

Publications

Citations

Publications by Year

20232023

Co-Authors:

Jörg Seewig

Author's Published Works

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Author details

Lukas Hacker

Lukas Hacker

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Publication Topics

Biography

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Insufficiency-Driven DNN Error Detection in the Context of SOTIF on Traffic Sign Recognition Use Case

Insufficiency-Driven DNN Error Detection in the Context of SOTIF on Traffic Sign Recognition Use Case

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Lukas Hacker

Lukas Hacker

Affiliation

Publication Topics

Biography

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Insufficiency-Driven DNN Error Detection in the Context of SOTIF on Traffic Sign Recognition Use Case

Insufficiency-Driven DNN Error Detection in the Context of SOTIF on Traffic Sign Recognition Use Case