Performance Analysis of Out-of-Distribution Detection on Trained Neural Networks

no code implementations • 26 Apr 2022 • Jens Henriksson, Christian Berger, Markus Borg, Lars Tornberg, Sankar Raman Sathyamoorthy, Cristofer Englund

Implementing Deep Neural Networks (DNN) for non-safety related applications have shown remarkable achievements over the past years; however, for using DNNs in safety critical applications, we are missing approaches for verifying the robustness of such models.

Outlier Detection Out-of-Distribution Detection

Performance Analysis of Out-of-Distribution Detection on Various Trained Neural Networks

no code implementations • 29 Mar 2021 • Jens Henriksson, Christian Berger, Markus Borg, Lars Tornberg, Sankar Raman Sathyamoorthy, Cristofer Englund

Understanding the relationship between training results and supervisor performance is valuable to improve robustness of the model and indicates where more work has to be done to create generalized models for safety critical applications.

Outlier Detection Out-of-Distribution Detection

Automated Augmentation with Reinforcement Learning and GANs for Robust Identification of Traffic Signs using Front Camera Images

no code implementations • 15 Nov 2019 • Sohini Roy Chowdhury, Lars Tornberg, Robin Halvfordsson, Jonatan Nordh, Adam Suhren Gustafsson, Joel Wall, Mattias Westerberg, Adam Wirehed, Louis Tilloy, Zhanying Hu, Haoyuan Tan, Meng Pan, Jonas Sjoberg

Traffic sign identification using camera images from vehicles plays a critical role in autonomous driving and path planning.

Autonomous Driving Generative Adversarial Network +1

Towards Structured Evaluation of Deep Neural Network Supervisors

no code implementations • 4 Mar 2019 • Jens Henriksson, Christian Berger, Markus Borg, Lars Tornberg, Cristofer Englund, Sankar Raman Sathyamoorthy, Stig Ursing

Deep Neural Networks (DNN) have improved the quality of several non-safety related products in the past years.