3 papers
cs.CV2023
Improving Data Efficiency for Plant Cover Prediction with Label Interpolation and Monte-Carlo Cropping
Matthias Körschens, Solveig Franziska Bucher, Christine Römermann +1
The plant community composition is an essential indicator of environmental changes and is, for this reason, usually analyzed in ecological field studies in terms of the so-called p…
cs.CV2021
Domain Adaptation and Active Learning for Fine-Grained Recognition in the Field of Biodiversity
Bernd Gruner, Matthias Körschens, Björn Barz +1
Deep-learning methods offer unsurpassed recognition performance in a wide range of domains, including fine-grained recognition tasks. However, in most problem areas there are insuf…
cs.CV2021
Automatic Plant Cover Estimation with Convolutional Neural Networks
Matthias Körschens, Paul Bodesheim, Christine Römermann +4
Monitoring the responses of plants to environmental changes is essential for plant biodiversity research. This, however, is currently still being done manually by botanists in the…