131 citations
- University of BonnDE5 papers
- Technical University of MunichDE2 papers
- Advanced Neural Dynamics (United States)US1 paper
- Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und MeeresforschungDE1 paper
- Berlin Institute of Health at Charité - Universitätsmedizin BerlinDE1 paper
- Deutsches Zentrum für Luft- und Raumfahrt e. V. (DLR)DE1 paper
- DKFZ-ZMBH AllianceDE1 paper
- Eindhoven University of TechnologyNL1 paper
- Federal Agency for Cartography and GeodesyDE1 paper
- Federal Institute For Materials Research and TestingDE1 paper
- FIZ Karlsruhe – Leibniz Institute for Information InfrastructureDE1 paper
- Friedrich Schiller University JenaDE1 paper
9 papers
Tomato Multi-Angle Multi-Pose Dataset for Fine-Grained Phenotyping
Yujie Zhang, Sabine Struckmeyer, Andreas Kolb +1
Observer bias and inconsistencies in traditional plant phenotyping methods limit the accuracy and reproducibility of fine-grained plant analysis. To overcome these challenges, we d…
Opinion models, data, and politics
Matthias Gsänger, Volker Hösel, Christoph Mohamad-Klotzbach +1
We investigate the connection between Potts (Curie-Weiss) models and stochastic opinion models in the view of the Boltzmann distribution and stochastic Glauber dynamics. We particu…
Behind the leaves -- Estimation of occluded grapevine berries with conditional generative adversarial networks
Jana Kierdorf, Immanuel Weber, Anna Kicherer +3
The need for accurate yield estimates for viticulture is becoming more important due to increasing competition in the wine market worldwide. One of the most promising methods to es…
An Environment for Sustainable Research Software in Germany and Beyond: Current State, Open Challenges, and Call for Action
Hartwig Anzt, Felix Bach, Stephan Druskat +40
Research software has become a central asset in academic research. It optimizes existing and enables new research methods, implements and embeds research knowledge, and constitutes…
Counting of Grapevine Berries in Images via Semantic Segmentation using Convolutional Neural Networks
Laura Zabawa, Anna Kicherer, Lasse Klingbeil +3
The extraction of phenotypic traits is often very time and labour intensive. Especially the investigation in viticulture is restricted to an on-site analysis due to the perennial n…
Efficient identification, localization and quantification of grapevine inflorescences in unprepared field images using Fully Convolutional Networks
Robert Rudolph, Katja Herzog, Reinhard Töpfer +1
Yield and its prediction is one of the most important tasks in grapevine breeding purposes and vineyard management. Commonly, this trait is estimated manually right before harvest…