Journal Article

Transparent exploration of machine learning for biomarker discovery from proteomics and omics data
Biomarkers are of central importance for assessing the health state and to guide medical interventions and their efficacy; still, they …
Furkan M. Torun, Sebastian Virreira Winter, Sophia Doll, Felix Riese, Artem Vorobyev, Johannes B. Mueller-Reif, Philipp E. Geyer, Maximilian T. Strauss
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Transparent exploration of machine learning for biomarker discovery from proteomics and omics data
Deep Learning for Land Cover Change Detection
Land cover and its change are crucial for many environmental applications. This study focuses on the land cover classification and …
Oliver Sefrin, Felix Riese, Sina Keller
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Deep Learning for Land Cover Change Detection
Supervised and Semi-Supervised Self-Organizing Maps for Regression and Classification Focusing on Hyperspectral Data
Machine learning approaches are valuable methods in hyperspectral remote sensing, especially for the classification of land cover or …
Felix Riese, Sina Keller, Stefan Hinz
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Supervised and Semi-Supervised Self-Organizing Maps for Regression and Classification Focusing on Hyperspectral Data
Soil Texture Classification with 1D Convolutional Neural Networks based on Hyperspectral Data
Soil texture is important for many environmental processes. In this paper, we study the classification of soil texture based on …
Felix Riese, Sina Keller
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Soil Texture Classification with 1D Convolutional Neural Networks based on Hyperspectral Data
Developing a machine learning framework for estimating soil moisture with VNIR hyperspectral data
In this paper, we investigate the potential of estimating the soil-moisture content based on VNIR hyperspectral data combined with IR …
Sina Keller, Felix Riese, Johanna Stötzer, Philipp M. Maier, Stefan Hinz
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Developing a machine learning framework for estimating soil moisture with VNIR hyperspectral data
Hyperspectral Data and Machine Learning for Estimating CDOM, Chlorophyll a, Diatoms, Green Algae, and Turbidity
Inland waters are of great importance for scientists as well as authorities since they are essential ecosystems and well known for …
Sina Keller, Philipp M. Maier, Felix Riese, Steffen Norra, Andreas Holbach, Nicolas Börsig, Andre Wilhelms, Christian Moldaenke, Andre Zaake, Stefan Hinz
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Hyperspectral Data and Machine Learning for Estimating CDOM, Chlorophyll a, Diatoms, Green Algae, and Turbidity