Andreas Margraf

Orcid: 0000-0002-2144-0262

According to our database1, Andreas Margraf authored at least 13 papers between 2017 and 2024.

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

Timeline

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Bibliography

2024
Analysing the Influence of Reorder Strategies for Cartesian Genetic Programming.
CoRR, 2024

2023
Model-Driven Optimisation of Monitoring System Configurations for Batch Production.
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.
Proceedings of the 15th International Joint Conference on Computational Intelligence, 2023

Towards Understanding Crossover for Cartesian Genetic Programming.
Proceedings of the 15th International Joint Conference on Computational Intelligence, 2023

Equidistant Reorder Operator for Cartesian Genetic Programming.
Proceedings of the 15th International Joint Conference on Computational Intelligence, 2023

Weighted Mutation of Connections To Mitigate Search Space Limitations in Cartesian Genetic Programming.
Proceedings of the 17th ACM/SIGEVO Conference on Foundations of Genetic Algorithms, 2023

Evolving Processing Pipelines for Industrial Imaging with Cartesian Genetic Programming.
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.
Proceedings of the 14th International Joint Conference on Computational Intelligence, 2022

Refining Mutation Variants in Cartesian Genetic Programming.
Proceedings of the Bioinspired Optimization Methods and Their Applications, 2022

2021
Alternative Data Augmentation for Industrial Monitoring Using Adversarial Learning.
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.
Proceedings of the 1st International Conference on Deep Learning Theory and Applications, 2020

Towards Self-adaptive Defect Classification in Industrial Monitoring.
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.
Proceedings of the 16th IEEE International Conference on Machine Learning and Applications, 2017


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