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Stefan Paulus
Stefan Paulus
Institute of Sugar Beet Research
Verified email at ifz-goettingen.de
Title
Cited by
Cited by
Year
Low-cost 3D systems: suitable tools for plant phenotyping
S Paulus, J Behmann, AK Mahlein, L Plümer, H Kuhlmann
Sensors 14 (2), 3001-3018, 2014
2572014
Surface feature based classification of plant organs from 3D laserscanned point clouds for plant phenotyping
S Paulus, J Dupuis, AK Mahlein, H Kuhlmann
BMC bioinformatics 14 (1), 1-12, 2013
1992013
High-precision laser scanning system for capturing 3D plant architecture and analysing growth of cereal plants
S Paulus, H Schumann, H Kuhlmann, J Léon
Biosystems Engineering 121, 1-11, 2014
1942014
Fusion of sensor data for the detection and differentiation of plant diseases in cucumber
CA Berdugo, R Zito, S Paulus, AK Mahlein
Plant pathology 63 (6), 1344-1356, 2014
1092014
Accuracy analysis of a multi-view stereo approach for phenotyping of tomato plants at the organ level
JC Rose, S Paulus, H Kuhlmann
Sensors 15 (5), 9651-9665, 2015
1062015
Automated analysis of barley organs using 3D laser scanning: An approach for high throughput phenotyping
S Paulus, J Dupuis, S Riedel, H Kuhlmann
Sensors 14 (7), 12670-12686, 2014
962014
Measuring crops in 3D: using geometry for plant phenotyping
S Paulus
Plant Methods 15 (1), 1-13, 2019
942019
Automated interpretation of 3D laserscanned point clouds for plant organ segmentation
M Wahabzada, S Paulus, K Kersting, AK Mahlein
BMC bioinformatics 16 (1), 1-11, 2015
812015
Generation and application of hyperspectral 3D plant models: methods and challenges
J Behmann, AK Mahlein, S Paulus, J Dupuis, H Kuhlmann, EC Oerke, ...
Machine Vision and Applications 27 (5), 611-624, 2016
782016
Calibration of hyperspectral close-range pushbroom cameras for plant phenotyping
J Behmann, AK Mahlein, S Paulus, H Kuhlmann, EC Oerke, L Plümer
ISPRS Journal of Photogrammetry and Remote Sensing 106, 172-182, 2015
682015
Limits of active laser triangulation as an instrument for high precision plant imaging
S Paulus, T Eichert, HE Goldbach, H Kuhlmann
Sensors 14 (2), 2489-2509, 2014
352014
Extending hyperspectral imaging for plant phenotyping to the UV-range
A Brugger, J Behmann, S Paulus, HG Luigs, MT Kuska, P Schramowski, ...
Remote Sensing 11 (12), 1401, 2019
272019
Spatial referencing of hyperspectral images for tracing of plant disease symptoms
J Behmann, D Bohnenkamp, S Paulus, AK Mahlein
Journal of Imaging 4 (12), 143, 2018
212018
Hyperspectral imaging of symptoms induced by Rhizoctonia solani in sugar beet: Comparison of input data and different machine learning algorithms
A Barreto, S Paulus, M Varrelmann, AK Mahlein
Journal of Plant Diseases and Protection 127 (4), 441-451, 2020
192020
Technical workflows for hyperspectral plant image assessment and processing on the greenhouse and laboratory scale
S Paulus, AK Mahlein
GigaScience 9 (8), giaa090, 2020
182020
A multi-resolution approach for an automated fusion of different low-cost 3D sensors
J Dupuis, S Paulus, J Behmann, L Plümer, H Kuhlmann
Sensors 14 (4), 7563-7579, 2014
172014
Pheno4D: A spatio-temporal dataset of maize and tomato plant point clouds for phenotyping and advanced plant analysis
D Schunck, F Magistri, RA Rosu, A Cornelißen, N Chebrolu, S Paulus, ...
Plos one 16 (8), e0256340, 2021
132021
Generation and application of hyperspectral 3D plant models
J Behmann, AK Mahlein, S Paulus, H Kuhlmann, EC Oerke, L Plümer
European Conference on Computer Vision, 117-130, 2014
122014
Spectral signatures in the UV range can be combined with secondary plant metabolites by deep learning to characterize barley–powdery mildew interaction
A Brugger, P Schramowski, S Paulus, U Steiner, K Kersting, AK Mahlein
Plant Pathology 70 (7), 1572-1582, 2021
72021
Prediction of the kiwifruit decline syndrome in diseased orchards by remote sensing
F Savian, M Martini, P Ermacora, S Paulus, AK Mahlein
Remote Sensing 12 (14), 2194, 2020
72020
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