no code implementations • 27 Nov 2023 • Maurice Günder, Sneha Banerjee, Rafet Sifa, Christian Bauckhage
Model-agnostic explanation methods for deep learning models are flexible regarding usability and availability.
no code implementations • 6 Nov 2023 • Maurice Günder, Facundo Ramón Ispizua Yamati, Abel Andree Barreto Alcántara, Anne-Katrin Mahlein, Rafet Sifa, Christian Bauckhage
One novelty in this work is the combination of remote sensing data with environmental parameters of the experimental sites for disease severity prediction.
no code implementations • 5 Sep 2022 • Maurice Günder, Nico Piatkowski, Christian Bauckhage
The concept of Label Distribution Learning (LDL) is a technique to stabilize classification and regression problems with ambiguous and/or imbalanced labels.
1 code implementation • 8 Jan 2022 • Maurice Günder, Facundo R. Ispizua Yamati, Jana Kierdorf, Ribana Roscher, Anne-Katrin Mahlein, Christian Bauckhage
Our workflow is able to automatize plant cataloging and training image extraction, especially for large datasets.