45 citations · 264 across the 36 of their papers we have counts for
39 papers
An Industrial Experience Report about Challenges from Continuous Monitoring, Improvement, and Deployment for Autonomous Driving Features
Ali Nouri, Christian Berger, Fredrik Torner
Using continuous development, deployment, and monitoring (CDDM) to understand and improve applications in a customer's context is widely used for non-safety applications such as sm…
Evaluation of Out-of-Distribution Detection Performance on Autonomous Driving Datasets
Jens Henriksson, Christian Berger, Stig Ursing +1
Safety measures need to be systemically investigated to what extent they evaluate the intended performance of Deep Neural Networks (DNNs) for critical applications. Due to a lack o…
RE-centric Recommendations for the Development of Trustworthy(er) Autonomous Systems
Krishna Ronanki, Beatriz Cabrero-Daniel, Jennifer Horkoff +1
Complying with the EU AI Act (AIA) guidelines while developing and implementing AI systems will soon be mandatory within the EU. However, practitioners lack actionable instructions…
Digital Sovereignty and Software Engineering for the IoT-laden, AI/ML-driven Era
Christian Berger
Today's software engineering already needs to deal with challenges originating from the multidisciplinarity that is required to realize IoT products: Many variants consist of senso…
Understanding the Impact of Edge Cases from Occluded Pedestrians for ML Systems
Jens Henriksson, Christian Berger, Stig Ursing
Machine learning (ML)-enabled approaches are considered a substantial support technique of detection and classification of obstacles of traffic participants in self-driving vehicle…
Performance Analysis of Out-of-Distribution Detection on Trained Neural Networks
Jens Henriksson, Christian Berger, Markus Borg +3
Several areas have been improved with Deep Learning during the past years. Implementing Deep Neural Networks (DNN) for non-safety related applications have shown remarkable achieve…