100 citations
- Osnabrück UniversityDE31 papers
- Bielefeld UniversityDE3 papers
- German Research Centre for Artificial IntelligenceDE3 papers
- University of WürzburgDE3 papers
- Institute of Inorganic Chemistry of the Slovak Academy of SciencesSK2 papers
- Johannes Gutenberg University MainzDE2 papers
- L3S Research CenterDE2 papers
- Landscape InstituteGB2 papers
- Leibniz Institute for Agricultural Engineering and BioeconomyDE2 papers
- Plant (United States)US2 papers
- Ruhr West University of Applied SciencesDE2 papers
- The Ohio State UniversityUS2 papers
8 papers · 1 filter
On the Maximal Dimension of Random Simplicial Complexes
Kinga Nagy
The dimension of random simplicial complexes (defined as the maximal dimension among all faces) is a natural extreme value associated with the complex, and is closely related to ot…
Toward an Agricultural Operational Design Domain: A Framework
Mirco Felske, Jannik Redenius, Georg Happich +1
The agricultural sector increasingly relies on autonomous systems that operate in complex and variable environments. Unlike on-road applications, agricultural automation integrates…
Depth Profiling of Oxygen Migration in Ta/HfO2 Stacks During Ionic Liquid Gating
Beatrice Bednarz, Martin Wortmann, Olga Kuschel +6
Ionic liquid (IL) gating has emerged as a powerful tool to control the structural, electronic, optical, and magnetic properties of materials by driving ion motion at solid interfac…
Kriging prior Regression: A Case for Kriging-Based Spatial Features with TabPFN in Soil Mapping
Jonas Schmidinger, Viacheslav Barkov, Sebastian Vogel +2
Machine learning and geostatistics are two fundamentally different frameworks for predicting and spatially mapping soil properties. Geostatistics leverages the spatial structure of…
Transferring Styles for Reduced Texture Bias and Improved Robustness in Semantic Segmentation Networks
Ben Hamscher, Edgar Heinert, Annika Mütze +2
Recent research has investigated the shape and texture biases of deep neural networks (DNNs) in image classification which influence their generalization capabilities and robustnes…
Modern Neural Networks for Small Tabular Datasets: The New Default for Field-Scale Digital Soil Mapping?
Viacheslav Barkov, Jonas Schmidinger, Robin Gebbers +1
In the field of pedometrics, tabular machine learning is the predominant method for soil property prediction from remote and proximal soil sensing data, forming a central component…