Lorenz Klampfl

Orcid: 0000-0003-2860-5098

According to our database1, Lorenz Klampfl authored at least 13 papers between 2019 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

2019
2020
2021
2022
2023
2024
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Legend:

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Article 
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Links

Online presence:

On csauthors.net:

Bibliography

2024
Testing ADAS/ADS - from critical scenarios to automated testing oracles.
Elektrotech. Informationstechnik, November, 2024

Using genetic algorithms for automating automated lane-keeping system testing.
J. Softw. Evol. Process., March, 2024

Knowledge-Based Monitoring for Checking Law and Regulation Compliance.
Proceedings of the Advances and Trends in Artificial Intelligence. Theory and Applications, 2024

Leveraging Answer Set Programming for Continuous Monitoring, Fault Detection, and Explanation of Automated and Autonomous Driving Systems.
Proceedings of the 35th International Conference on Principles of Diagnosis and Resilient Systems, 2024

2023
Identifying Critical Scenarios in Autonomous Driving During Operation.
Proceedings of the Artificial Intelligence. ECAI 2023 International Workshops - XAI³, TACTIFUL, XI-ML, SEDAMI, RAAIT, AI4S, HYDRA, AI4AI, Kraków, Poland, September 30, 2023

2021
Automatic Generation of Challenging Road Networks for ALKS Testing based on Bezier Curves and Search.
CoRR, 2021

Extracting information from driving data using k-means clustering (S).
Proceedings of the 33rd International Conference on Software Engineering and Knowledge Engineering, 2021

GABezier at the SBST 2021 Tool Competition.
Proceedings of the 14th IEEE/ACM International Workshop on Search-Based Software Testing, 2021

A framework for the automation of testing computer vision systems.
Proceedings of the 2nd IEEE/ACM International Conference on Automation of Software Test, 2021

Critical and Challenging Scenario Generation based on Automatic Action Behavior Sequence Optimization: 2021 IEEE Autonomous Driving AI Test Challenge Group 108.
Proceedings of the 2021 IEEE International Conference on Artificial Intelligence Testing, 2021

2020
Mutation Testing for Artificial Neural Networks: An Empirical Evaluation.
Proceedings of the 20th IEEE International Conference on Software Quality, 2020

Explaining Object Motion Using Answer Set Programming.
Proceedings of the Foundations of Intelligent Systems - 25th International Symposium, 2020

2019
Investigating the Effectiveness of Mutation Testing Tools in the Context of Deep Neural Networks.
Proceedings of the Advances in Computational Intelligence, 2019


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