activity
20192022
most citedPerformance Analysis of Out-of-Distribution Detection on Trained Neural Networks

16 citations · 18 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2022

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…

cs.LG202216 cited

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…

cs.LG2021

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…

cs.LG2020

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…

cs.LG20192 cited

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…