Reinhard Töpfer

Orcid: 0000-0003-1569-2495

According to our database1, Reinhard Töpfer authored at least 19 papers between 2015 and 2023.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

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Links

On csauthors.net:

Bibliography

2023
Determination of Sugars and Acids in Grape Must Using Miniaturized Near-Infrared Spectroscopy.
Sensors, 2023

Grouping Shapley Value Feature Importances of Random Forests for explainable Yield Prediction.
CoRR, 2023

2020
Detection of Grapevine Leafroll-Associated Virus 1 and 3 in White and Red Grapevine Cultivars Using Hyperspectral Imaging.
Remote. Sens., 2020

Detection of Two Different Grapevine Yellows in Vitis vinifera Using Hyperspectral Imaging.
Remote. Sens., 2020

Counting of Grapevine Berries in Images via Semantic Segmentation using Convolutional Neural Networks.
CoRR, 2020

2019
Combination of an Automated 3D Field Phenotyping Workflow and Predictive Modelling for High-Throughput and Non-Invasive Phenotyping of Grape Bunches.
Remote. Sens., 2019

Automated phenotyping of epicuticular waxes of grapevine berries using light separation and convolutional neural networks.
Comput. Electron. Agric., 2019

Detection of Single Grapevine Berries in Images Using Fully Convolutional Neural Networks.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2019

2018
High-Precision Phenotyping of Grape Bunch Architecture Using Fast 3D Sensor and Automation.
Sensors, 2018

An Adaptive Approach for Automated Grapevine Phenotyping using VGG-based Convolutional Neural Networks.
CoRR, 2018

Efficient identification, localization and quantification of grapevine inflorescences in unprepared field images using Fully Convolutional Networks.
CoRR, 2018

Multi-View Semantic Labeling of 3D Point Clouds for Automated Plant Phenotyping.
CoRR, 2018

Semantic labeling and reconstruction of grape bunches from 3D range data using a new RGB-D feature descriptor.
Comput. Electron. Agric., 2018

2017
Phenoliner: A New Field Phenotyping Platform for Grapevine Research.
Sensors, 2017

Automated Image Analysis Framework for the High-Throughput Determination of Grapevine Berry Sizes Using Conditional Random Fields.
CoRR, 2017

2016
Towards Automated Large-Scale 3D Phenotyping of Vineyards under Field Conditions.
Sensors, 2016

2015
An Automated Field Phenotyping Pipeline for Application in Grapevine Research.
Sensors, 2015

Impedance of the Grape Berry Cuticle as a Novel Phenotypic Trait to Estimate Resistance to<i> Botrytis Cinerea</i>.
Sensors, 2015

Field phenotyping of grapevine growth using dense stereo reconstruction.
BMC Bioinform., 2015


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