Papers
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Using Machine Learning for Optical Spectroscopy Data Analysis
Birk Martin Magnussen
2024.11 [Refereed]
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S-MSRRS5000: A Simulated Dataset Highlighting the Challenges of Data Obtained From Multiple Spatially Resolved Reflection Spectroscopy
Birk Martin Magnussen, Maik Jessulat, Claudius Stern, Bernhard Sick
2024.04
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Birk Martin Magnussen, Frank Möckel, Maik Jessulat, Claudius Stern, Bernhard Sick
2024 12th International Conference on Bioinformatics and Computational Biology (ICBCB) 132 - 136 2024.03 [Refereed]
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Birk Martin Magnussen, Maik Jessulat, Claudius Stern, Bernhard Sick
2024 9th International Conference on Big Data Analytics (ICBDA) 305 - 310 2024.03 [Refereed]
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Birk Martin Magnussen, Claudius Stern, Bernhard Sick
International Journal On Advances in Intelligent Systems 16 ( 3\&4 ) 43 - 50 2023.12 [Refereed] [Invited]
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Leveraging Repeated Unlabelled Noisy Measurements to Augment Supervised Learning
Birk Martin Magnussen, Claudius Stern, Bernhard Sick
Proceedings of the 2023 6th International Conference on Computational Intelligence and Intelligent Systems 1 - 6 2023.11 [Refereed]
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Intra-Model Smoothing Using Depth Aware Multi-Sample Anti-Aliasing for Deferred Rendering Pipelines
Birk Martin Magnussen
Computer Graphics & Visual Computing (CGVC) 2023 2023.09 [Refereed] [International journal]
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Birk Martin Magnussen, Claudius Stern, Bernhard Sick
Proceedings of The Nineteenth International Conference on Autonomic and Autonomous Systems 49 - 53 2023.03 [Refereed]
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Performance Evaluation of OSCAR Multi-target Automatic Parallelizing Compiler on Intel, AMD, Arm and RISC-V Multicores
Birk Martin Magnussen, Tohma Kawasumi, Hiroki Mikami, Keiji Kimura, Hironori Kasahara
Languages and Compilers for Parallel Computing 50 - 64 2022 [Refereed]
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