131 citations · 225 across the 4 of their papers we have counts for
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Counting of Grapevine Berries in Images via Semantic Segmentation using Convolutional Neural Networks
Laura Zabawa, Anna Kicherer, Lasse Klingbeil +3
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 n…
Detection of Single Grapevine Berries in Images Using Fully Convolutional Neural Networks
Laura Zabawa, Anna Kicherer, Lasse Klingbeil +4
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 t…
An Adaptive Approach for Automated Grapevine Phenotyping using VGG-based Convolutional Neural Networks
Jonatan Grimm, Katja Herzog, Florian Rist +3
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…
Automated Image Analysis Framework for the High-Throughput Determination of Grapevine Berry Sizes Using Conditional Random Fields
Ribana Roscher, Katja Herzog, Annemarie Kunkel +3
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 g…