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
Showing 2018Show all
3 papers · 1 filter
cs.CV2018★ 6 cited
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…
cs.CV2018
Automated Phenotyping of Epicuticular Waxes of Grapevine Berries Using Light Separation and Convolutional Neural Networks
Pierre Barré, Katja Herzog, Rebecca Höfle +3
In viticulture the epicuticular wax as the outer layer of the berry skin is known as trait which is correlated to resilience towards Botrytis bunch rot. Traditionally this trait is…
cs.CV2018★ 2 cited
Multi-View Semantic Labeling of 3D Point Clouds for Automated Plant Phenotyping
Bernhard Japes, Jennifer Mack, Florian Rist +3
Semantic labeling of 3D point clouds is important for the derivation of 3D models from real world scenarios in several economic fields such as building industry, facility managemen…