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Functional Plant Biology : FPB|June 3, 2020
Sensors and imaging techniques for the assessment of the delay of wheat senescence induced by fungicidesCarlos Andres Berdugo, Anne-Katrin Mahlein, Ulrike Steiner, et al.
Toxins|September 25, 2019
Assessment of <i>Fusarium</i> Infection and Mycotoxin Contamination of Wheat Kernels and Flour Using Hyperspectral ImagingElias Alisaac, Jan Behmann, Anna Rathgeb, et al.
Scientific Reports|March 10, 2016
Plant Phenotyping using Probabilistic Topic Models: Uncovering the Hyperspectral Language of PlantsMirwaes Wahabzada, Anne-Katrin Mahlein, Christian Bauckhage, et al.
Plos One|January 27, 2015
Metro maps of plant disease dynamics--automated mining of differences using hyperspectral imagesMirwaes Wahabzada, Anne-Katrin Mahlein, Christian Bauckhage, et al.
Sensors (Basel, Switzerland)|June 4, 2015
Supplemental blue LED lighting array to improve the signal quality in hyperspectral imaging of plantsAnne-Katrin Mahlein, Simon Hammersley, Erich-Christian Oerke, et al.
Gigascience|June 17, 2022
Agricultural plant cataloging and establishment of a data framework from UAV-based crop images by computer visionMaurice Günder, Facundo R Ispizua Yamati, Jana Kierdorf, et al.
BMC Bioinformatics|July 31, 2020
Statistical shape analysis of tap roots: a methodological case study on laser scanned sugar beetsBehrend Heeren, Stefan Paulus, Heiner Goldbach, et al.
Plant Methods|June 23, 2018
Quantitative assessment of disease severity and rating of barley cultivars based on hyperspectral imaging in a non-invasive, automated phenotyping platformStefan Thomas, Jan Behmann, Angelina Steier, et al.
Plos One|March 20, 2019
Discovering coherency of specific gene expression and optical reflectance properties of barley genotypes differing for resistance reactions against powdery mildewMatheus Thomas Kuska, Jan Behmann, Mahsa Namini, et al.
Plos One|February 13, 2025
SugarViT-Multi-objective regression of UAV images with Vision Transformers and Deep Label Distribution Learning demonstrated on disease severity prediction in sugar beetMaurice Günder, Facundo Ramón Ispizua Yamati, Abel Barreto, et al.
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