16 citations · 19 across the 7 of their papers we have counts for
7 papers
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…
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…
Ergo, SMIRK is Safe: A Safety Case for a Machine Learning Component in a Pedestrian Automatic Emergency Brake System
Markus Borg, Jens Henriksson, Kasper Socha +7
Integration of Machine Learning (ML) components in critical applications introduces novel challenges for software certification and verification. New safety standards and technical…
Performance Analysis of Out-of-Distribution Detection on Various Trained Neural Networks
Jens Henriksson, Christian Berger, Markus Borg +3
Several areas have been improved with Deep Learning during the past years. For non-safety related products adoption of AI and ML is not an issue, whereas in safety critical applica…
Controlled time series generation for automotive software-in-the-loop testing using GANs
Dhasarathy Parthasarathy, Karl Bäckström, Jens Henriksson +1
Testing automotive mechatronic systems partly uses the software-in-the-loop approach, where systematically covering inputs of the system-under-test remains a major challenge. In cu…
Towards Structured Evaluation of Deep Neural Network Supervisors
Jens Henriksson, Christian Berger, Markus Borg +4
Deep Neural Networks (DNN) have improved the quality of several non-safety related products in the past years. However, before DNNs should be deployed to safety-critical applicatio…