Counting of grapevine berries in images via semantic segmentation using convolutional neural networks L Zabawa, A Kicherer, L Klingbeil, R Töpfer, H Kuhlmann, R Roscher ISPRS Journal of Photogrammetry and Remote Sensing 164, 73-83, 2020 | 87 | 2020 |
Detection of single grapevine berries in images using fully convolutional neural networks L Zabawa, A Kicherer, L Klingbeil, A Milioto, R Topfer, H Kuhlmann, ... Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019 | 44 | 2019 |
Behind the leaves: estimation of occluded grapevine berries with conditional generative adversarial networks J Kierdorf, I Weber, A Kicherer, L Zabawa, L Drees, R Roscher Frontiers in artificial intelligence 5, 830026, 2022 | 21 | 2022 |
Transfer learning from synthetic in-vitro soybean pods dataset for in-situ segmentation of on-branch soybean pods S Yang, L Zheng, X Chen, L Zabawa, M Zhang, M Wang Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 8 | 2022 |
Image-based analysis of yield parameters in viticulture L Zabawa, A Kicherer, L Klingbeil, R Töpfer, R Roscher, H Kuhlmann Biosystems Engineering 218, 94-109, 2022 | 6 | 2022 |
Behind the leaves—Estimation of occluded grapevine berries with conditional generative adversarial networks. arXiv 2021 J Kierdorf, I Weber, A Kicherer, L Zabawa, L Drees, R Roscher arXiv preprint arXiv:2105.10325, 0 | 5 | |
Detection of Anomalous Grapevine Berries Using Variational Autoencoders M Miranda, L Zabawa, A Kicherer, L Strothmann, U Rascher, R Roscher Frontiers in Plant Science 13, 729097, 2022 | 3 | 2022 |
Automatic differentiation of damaged and unharmed grapes using rgb images and convolutional neural networks J Bömer, L Zabawa, P Sieren, A Kicherer, L Klingbeil, U Rascher, ... Computer Vision–ECCV 2020 Workshops: Glasgow, UK, August 23–28, 2020 …, 2020 | 2 | 2020 |
Detection and counting of wheat ears by means of ground-based image acquisition. J Kierdorf, L Zabawa, L Lucks, L Klingbeil, H Kuhlmann Bornimer Agrartechnische Berichte, 158-167, 2019 | 1 | 2019 |
Contributions to image-based high-throughput phenotyping in viticulture L Zabawa Universitäts-und Landesbibliothek Bonn, 2023 | | 2023 |
UAV-based individual plant detection and geometric parameter extraction in vineyards M Cantürk, L Zabawa, D Pavlic, A Dreier, L Klingbeil, H Kuhlmann Frontiers in Plant Science 14, 2023 | | 2023 |
Development of multilevel monitoring systems for the identification of phytoplasma diseases in German viticultural areas B Jarausch, E Alisaac, P Schumacher, P Gauweiler, R Gruna, L Zabawa, ... Phytopathogenic Mollicutes 13 (1), 133-134, 2023 | | 2023 |
IPAS: Neue Anbausysteme für einen nachhaltigen Weinbau (NoViSys), Teilprojekt H: Veröffentlichung der Ergebnisse von Forschungsvorhaben im BMBF-Programm: Projektlaufzeit: 01.02 … H Kuhlmann, L Klingbeil, L Zabawa Rheinische Friedrich-Wilhelms-Universität Bonn, 2020 | | 2020 |
Detection of grapevine in images using fully convolutional Neural Nets. L Zabawa, A Kicherer, L Klingbeil, A Milioto, R Roscher, R Töpfer, ... Bornimer Agrartechnische Berichte, 15-20, 2019 | | 2019 |
Automated Surface Area Estimation of Plants based on 3D Point Clouds L Zabawa, L Zabawa, F Esser, L Klingbeil, H Kuhlmann | | |