Mirwaes Wahabzada
Mirwaes Wahabzada
BASF Digital Farming GmbH
Verified email at basf.com
Cited by
Cited by
Early drought stress detection in cereals: simplex volume maximisation for hyperspectral image analysis
C Römer, M Wahabzada, A Ballvora, F Pinto, M Rossini, C Panigada, ...
Functional Plant Biology 39 (11), 878-890, 2012
Hyperspectral phenotyping on the microscopic scale: towards automated characterization of plant-pathogen interactions
M Kuska, M Wahabzada, M Leucker, HW Dehne, K Kersting, EC Oerke, ...
Plant methods 11 (1), 28, 2015
Descriptive matrix factorization for sustainability adopting the principle of opposites
C Thurau, K Kersting, M Wahabzada, C Bauckhage
Data Mining and Knowledge Discovery 24 (2), 325-354, 2012
Metro maps of plant disease dynamics—automated mining of differences using hyperspectral images
M Wahabzada, AK Mahlein, C Bauckhage, U Steiner, EC Oerke, ...
Plos one 10 (1), e0116902, 2015
Benefits of hyperspectral imaging for plant disease detection and plant protection: a technical perspective
S Thomas, MT Kuska, D Bohnenkamp, A Brugger, E Alisaac, ...
Journal of Plant Diseases and Protection 125 (1), 5-20, 2018
Plant phenotyping using probabilistic topic models: uncovering the hyperspectral language of plants
M Wahabzada, AK Mahlein, C Bauckhage, U Steiner, EC Oerke, ...
Scientific reports 6 (1), 1-11, 2016
Automated interpretation of 3D laserscanned point clouds for plant organ segmentation
M Wahabzada, S Paulus, K Kersting, AK Mahlein
BMC bioinformatics 16 (1), 248, 2015
Convex non-negative matrix factorization for massive datasets
C Thurau, K Kersting, M Wahabzada, C Bauckhage
Knowledge and information systems 29 (2), 457-478, 2011
Hierarchical convex NMF for clustering massive data
K Kersting, M Wahabzada, C Thurau, C Bauckhage
Proceedings of 2nd Asian Conference on Machine Learning, 253-268, 2010
Observation of plant–pathogen interaction by simultaneous hyperspectral imaging reflection and transmission measurements
S Thomas, M Wahabzada, MT Kuska, U Rascher, AK Mahlein
Functional Plant Biology 44 (1), 23-34, 2017
Hyperspectral imaging reveals the effect of sugar beet quantitative trait loci on Cercospora leaf spot resistance
M Leucker, M Wahabzada, K Kersting, M Peter, W Beyer, U Steiner, ...
Functional Plant Biology 44 (1), 1-9, 2017
Spectral Patterns Reveal Early Resistance Reactions of Barley Against Blumeria graminis f. sp. hordei
MT Kuska, A Brugger, S Thomas, M Wahabzada, K Kersting, EC Oerke, ...
Phytopathology 107 (11), 1388-1398, 2017
Non-negative factor analysis supporting the interpretation of elemental distribution images acquired by XRF
M Alfeld, M Wahabzada, C Bauckhage, K Kersting, G Wellenreuther, ...
J Phys Conf Ser 499 (1), 012013, 2014
Monitoring wound healing in a 3D wound model by hyperspectral imaging and efficient clustering
M Wahabzada, M Besser, M Khosravani, MT Kuska, K Kersting, ...
PloS one 12 (12), e0186425, 2017
Larger residuals, less work: Active document scheduling for latent Dirichlet allocation
M Wahabzada, K Kersting
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2011
Pre-Symptomatic Prediction of Plant Drought Stress Using Dirichlet-Aggregation Regression on Hyperspectral Images.
K Kersting, Z Xu, M Wahabzada, C Bauckhage, C Thurau, C Roemer, ...
AAAI, 2012
Simplex distributions for embedding data matrices over time
K Kersting, M Wahabzada, C Römer, C Thurau, A Ballvora, U Rascher, ...
Proceedings of the 2012 SIAM international conference on data mining, 295-306, 2012
Plant disease detection by hyperspectral imaging: from the lab to the field
AK Mahlein, MT Kuska, S Thomas, D Bohnenkamp, E Alisaac, J Behmann, ...
Advances in Animal Biosciences 8 (2), 238-243, 2017
Topic models conditioned on relations
M Wahabzada, Z Xu, K Kersting
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2010
More influence means less work: fast latent Dirichlet allocation by influence scheduling
M Wahabzada, K Kersting, A Pilz, C Bauckhage
Proceedings of the 20th ACM international conference on Information and …, 2011
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Articles 1–20