Zobrazeno 1 - 10
of 484
pro vyhledávání: '"Kicherer A"'
Autor:
Huber, Florian, Engler, Hannes, Kicherer, Anna, Herzog, Katja, Töpfer, Reinhard, Steinhage, Volker
Explainability in yield prediction helps us fully explore the potential of machine learning models that are already able to achieve high accuracy for a variety of yield prediction scenarios. The data included for the prediction of yields are intricat
Externí odkaz:
http://arxiv.org/abs/2304.07111
Autor:
Lucie Cornehl, Pascal Gauweiler, Xiaorong Zheng, Julius Krause, Florian Schwander, Reinhard Töpfer, Robin Gruna, Anna Kicherer
Publikováno v:
Frontiers in Plant Science, Vol 15 (2024)
It is crucial for winegrowers to make informed decisions about the optimum time to harvest the grapes to ensure the production of premium wines. Global warming contributes to decreasing acidity and increasing sugar levels in grapes, resulting in blan
Externí odkaz:
https://doaj.org/article/b6fdf1fa5b524de3887c2bbd751d6c92
Publikováno v:
BIO Web of Conferences, Vol 5, p 01018 (2015)
Recently several papers appeared describing initial steps for novel phenotyping technologies in grapevine management, research and breeding. Kicherer and coworkers were the first using a robotic device which permits to follow a GPS track, stopping in
Externí odkaz:
https://doaj.org/article/9f2731d975494b2483049370aad5edf8
Autor:
Kierdorf, Jana, Weber, Immanuel, Kicherer, Anna, Zabawa, Laura, Drees, Lukas, Roscher, Ribana
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 estimate the harvest is berry counting, as it can be approached non-dest
Externí odkaz:
http://arxiv.org/abs/2105.10325
Autor:
Zabawa, Laura, Kicherer, Anna, Klingbeil, Lasse, Töpfer, Reinhard, Kuhlmann, Heiner, Roscher, Ribana
Publikováno v:
Journal of Photogrammetry and Remote Sensing, vol. 164, pp.73-83,2020
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 nature of grapevine. Traditionally skilled experts examine small sample
Externí odkaz:
http://arxiv.org/abs/2004.14010
Autor:
Zabawa, Laura, Kicherer, Anna, Klingbeil, Lasse, Milioto, Andres, Töpfer, Reinhard, Kuhlmann, Heiner, Roscher, Ribana
Publikováno v:
CVPR Workshop on Computer Vision Problems in Plant Phenotyping, 2019
Yield estimation and forecasting are of special interest in the field of grapevine breeding and viticulture. The number of harvested berries per plant is strongly correlated with the resulting quality. Therefore, early yield forecasting can enable a
Externí odkaz:
http://arxiv.org/abs/1905.00458
Akademický článek
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Autor:
Grimm, Jonatan, Herzog, Katja, Rist, Florian, Kicherer, Anna, Töpfer, Reinhard, Steinhage, Volker
In (grapevine) breeding programs and research, periodic phenotyping and multi-year monitoring of different grapevine traits, like growth or yield, is needed especially in the field. This demand imply objective, precise and automated methods using sen
Externí odkaz:
http://arxiv.org/abs/1811.09561
Autor:
Roscher, Ribana, Herzog, Katja, Kunkel, Annemarie, Kicherer, Anna, Töpfer, Reinhard, Förstner, Wolfgang
Publikováno v:
Computers and Electronics in Agriculture 100 (2014), 148--158
The berry size is one of the most important fruit traits in grapevine breeding. Non-invasive, image-based phenotyping promises a fast and precise method for the monitoring of the grapevine berry size. In the present study an automated image analyzing
Externí odkaz:
http://arxiv.org/abs/1712.05647
Autor:
Zabawa, Laura, Kicherer, Anna, Klingbeil, Lasse, Töpfer, Reinhard, Roscher, Ribana, Kuhlmann, Heiner
Publikováno v:
In Biosystems Engineering June 2022 218:94-109