Andreas Margraf

According to our database, Andreas Margraf authored at least 12 papers between 2017 and 2023.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2023

Model-Driven Optimisation of Monitoring System Configurations for Batch Production.

Andreas Margraf, Henning Cui, Simon Heimbach, Jörg Hähner, Steffen Geinitz, Stephan Rudolph

Proceedings of the 11th International Conference on Model-Based Software and Systems Engineering, 2023

Filter Evolution Using Cartesian Genetic Programming for Time Series Anomaly Detection.

Andreas Margraf, Henning Cui, Stefan Baumann, Jörg Hähner

Proceedings of the 15th International Joint Conference on Computational Intelligence, 2023

Towards Understanding Crossover for Cartesian Genetic Programming.

Henning Cui, Andreas Margraf, Michael Heider, Jörg Hähner

Proceedings of the 15th International Joint Conference on Computational Intelligence, 2023

Equidistant Reorder Operator for Cartesian Genetic Programming.

Henning Cui, Andreas Margraf, Jörg Hähner

Proceedings of the 15th International Joint Conference on Computational Intelligence, 2023

Weighted Mutation of Connections To Mitigate Search Space Limitations in Cartesian Genetic Programming.

Henning Cui, David Pätzel, Andreas Margraf, Jörg Hähner

Proceedings of the 17th ACM/SIGEVO Conference on Foundations of Genetic Algorithms, 2023

Evolving Processing Pipelines for Industrial Imaging with Cartesian Genetic Programming.

Andreas Margraf, Henning Cui, Anthony Stein, Jörg Hähner

Proceedings of the IEEE International Conference on Autonomic Computing and Self-Organizing Systems, 2023

2022

Signal Detection for Tracer-Based-Sorting using Deep Learning and Synthetic Data.

Christian Linder, Frank Gaibler, Andreas Margraf, Steffen Geinitz

Proceedings of the 14th International Joint Conference on Computational Intelligence, 2022

Refining Mutation Variants in Cartesian Genetic Programming.

Henning Cui, Andreas Margraf, Jörg Hähner

Proceedings of the Bioinspired Optimization Methods and Their Applications, 2022

2021

Alternative Data Augmentation for Industrial Monitoring Using Adversarial Learning.

Silvan Mertes, Andreas Margraf, Steffen Geinitz, Elisabeth André

Proceedings of the Deep Learning Theory and Applications, 2021

2020

Data Augmentation for Semantic Segmentation in the Context of Carbon Fiber Defect Detection using Adversarial Learning.

Silvan Mertes, Andreas Margraf, Christoph Kommer, Steffen Geinitz, Elisabeth André

Proceedings of the 1st International Conference on Deep Learning Theory and Applications, 2020

Towards Self-adaptive Defect Classification in Industrial Monitoring.

Andreas Margraf, Jörg Hähner, Philipp Braml, Steffen Geinitz

Proceedings of the 9th International Conference on Data Science, 2020

2017

An Evolutionary Learning Approach to Self-configuring Image Pipelines in the Context of Carbon Fiber Fault Detection.

Andreas Margraf, Anthony Stein, Leonhard Engstler, Steffen Geinitz, Jörg Hähner

Proceedings of the 16th IEEE International Conference on Machine Learning and Applications, 2017