Anne-Katrin Mahlein

Cytowane przez

	Wszystkie	Od 2017
Cytowania	6551	5532
h-indeks	36	35
i10-indeks	61	59

1400

700

350

1050

20112012201320142015201620172018201920202021202231 57 82 179 241 371 479 786 911 1140 1309 899

Dostęp publiczny

Wyświetl wszystko

31 artykułów

14 artykułów

dostępne

niedostępne

Objęte finansowaniem

Współautorzy

Dehne, H.-W.Prof. of Plant Pathology, University of BonnZweryfikowany adres z uni-bonn.de
Stefan PaulusInstitute of Sugar Beet ResearchZweryfikowany adres z ifz-goettingen.de
Matheus Thomas KuskaNorth Rhine-Westphalia Chamber of AgricultureZweryfikowany adres z uni-bonn.de
Lutz PlümerProfessor für Geoinformation, Universität BonnZweryfikowany adres z igg.uni-bonn.de
Kristian KerstingProfessor of AI & Machine Learning, TU Darmstadt, Co-Director of hessian.ai, Germany, CLAIRE & ELLISZweryfikowany adres z cs.tu-darmstadt.de
Mirwaes WahabzadaBASF Digital Farming GmbHZweryfikowany adres z basf.com
Heiner KuhlmannProfessor of Geodesy, University of BonnZweryfikowany adres z uni-bonn.de
Elias AlisaacJulius Kühn-InstitutZweryfikowany adres z julius-kuehn.de
Christian BauckhageProf. of Computer Science, University of Bonn, Fraunhofer IAISZweryfikowany adres z bit.uni-bonn.de
Uwe RascherProfessor of Quantitative Crop PhysiologyZweryfikowany adres z fz-juelich.de
Mark Varrelmann, Prof. for Plant Virolo...University of Götttingen, Inst. of Sugar Beet ResearchZweryfikowany adres z ifz-goettingen.de
Patrick SchramowskiTU DarmstadtZweryfikowany adres z cs.tu-darmstadt.de
Pascal WelkeUniversity of BonnZweryfikowany adres z uni-bonn.de
Jayme Garcia Arnal BarbedoResearcher, Empresa Brasileira de Pesquisa Agropecuária (Embrapa)Zweryfikowany adres z embrapa.br
Clive BockUSDA-ARSZweryfikowany adres z usda.gov
Emerson Del PonteProfessorZweryfikowany adres z ufv.br
Stefano TesoAssistant Professor, University of TrentoZweryfikowany adres z unitn.it
Wolfgang StammerTechnical University DarmstadtZweryfikowany adres z cs.tu-darmstadt.de
Achim WalterProfessor of Crop Science, ETH ZürichZweryfikowany adres z usys.ethz.ch
Gerrit PolderResearcher Image Analysis, Wageningen UniversityZweryfikowany adres z wur.nl

Obserwuj

Anne-Katrin Mahlein

Institute of Sugar Beet Reserach, Göttingen

Zweryfikowany adres z ifz-goettingen.de - Strona główna

plant diseases plant protection optical sensors plant phenotyping sugar beet


Tytuł Sortuj wg cytatów Sortuj wg roku Sortuj wg tytułu	Cytowane przez Cytowane przez	Rok
Early detection and classification of plant diseases with support vector machines based on hyperspectral reflectance T Rumpf, AK Mahlein, U Steiner, EC Oerke, HW Dehne, L Plümer Computers and electronics in agriculture 74 (1), 91-99, 2010	769	2010
Plant disease detection by imaging sensors–parallels and specific demands for precision agriculture and plant phenotyping AK Mahlein Plant disease 100 (2), 241-251, 2016	733	2016
Recent advances in sensing plant diseases for precision crop protection AK Mahlein, EC Oerke, U Steiner, HW Dehne European Journal of Plant Pathology 133 (1), 197-209, 2012	477	2012
Development of spectral indices for detecting and identifying plant diseases AK Mahlein, T Rumpf, P Welke, HW Dehne, L Plümer, U Steiner, ... Remote Sensing of Environment 128, 21-30, 2013	456	2013
Hyperspectral imaging for small-scale analysis of symptoms caused by different sugar beet diseases AK Mahlein, U Steiner, C Hillnhütter, HW Dehne, EC Oerke Plant methods 8 (1), 1-13, 2012	298	2012
A review of advanced machine learning methods for the detection of biotic stress in precision crop protection J Behmann, AK Mahlein, T Rumpf, C Römer, L Plümer Precision Agriculture 16 (3), 239-260, 2015	256	2015
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	253	2014
Spectral signatures of sugar beet leaves for the detection and differentiation of diseases AK Mahlein, U Steiner, HW Dehne, EC Oerke Precision agriculture 11 (4), 413-431, 2010	222	2010
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	197	2013
Hyperspectral sensors and imaging technologies in phytopathology: state of the art AK Mahlein, MT Kuska, J Behmann, G Polder, A Walter Annual review of phytopathology 56, 535-558, 2018	173	2018
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	159	2018
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), 1-15, 2015	156	2015
Remote sensing to detect plant stress induced by Heterodera schachtii and Rhizoctonia solani in sugar beet fields C Hillnhütter, AK Mahlein, RA Sikora, EC Oerke Field Crops Research 122 (1), 70-77, 2011	132	2011
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	116	2016
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	116	2015
Specim IQ: evaluation of a new, miniaturized handheld hyperspectral camera and its application for plant phenotyping and disease detection J Behmann, K Acebron, D Emin, S Bennertz, S Matsubara, S Thomas, ... Sensors 18 (2), 441, 2018	108	2018
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	108	2014
Airborne hyperspectral imaging of spatial soil organic carbon heterogeneity at the field-scale C Hbirkou, S Pätzold, AK Mahlein, G Welp Geoderma 175, 21-28, 2012	90	2012
Quantitative assessment of disease severity and rating of barley cultivars based on hyperspectral imaging in a non-invasive, automated phenotyping platform S Thomas, J Behmann, A Steier, T Kraska, O Muller, U Rascher, ... Plant methods 14 (1), 1-12, 2018	84	2018
Making deep neural networks right for the right scientific reasons by interacting with their explanations P Schramowski, W Stammer, S Teso, A Brugger, F Herbert, X Shao, ... Nature Machine Intelligence 2 (8), 476-486, 2020	82	2020

Nie można teraz wykonać tej operacji. Spróbuj ponownie później.

Prace 1–20

Cytowania rocznie

Powielone cytowania

Scalone cytowania

Dodaj współautorówWspółautorzy

Obserwuj

Cytowane przez

Współautorzy