Hanno Scharr
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Simultaneous phenotyping of leaf growth and chlorophyll fluorescence via GROWSCREEN FLUORO allows detection of stress tolerance in Arabidopsis thaliana and other rosette plants
M Jansen, F Gilmer, B Biskup, KA Nagel, U Rascher, A Fischbach, ...
Functional Plant Biology 36 (11), 902-914, 2009
GROWSCREEN-Rhizo is a novel phenotyping robot enabling simultaneous measurements of root and shoot growth for plants grown in soil-filled rhizotrons
KA Nagel, A Putz, F Gilmer, K Heinz, A Fischbach, J Pfeifer, M Faget, ...
Functional plant biology 39 (11), 891-904, 2012
A scheme for coherence-enhancing diffusion filtering with optimized rotation invariance
J Weickert, H Scharr
Journal of Visual Communication and Image Representation 13 (1-2), 103-118, 2002
Finely-grained annotated datasets for image-based plant phenotyping
M Minervini, A Fischbach, H Scharr, SA Tsaftaris
Pattern recognition letters 81, 80-89, 2016
Leaf segmentation in plant phenotyping: a collation study
H Scharr, M Minervini, AP French, C Klukas, DM Kramer, X Liu, I Luengo, ...
Machine vision and applications 27, 585-606, 2016
Temperature responses of roots: impact on growth, root system architecture and implications for phenotyping
KA Nagel, B Kastenholz, S Jahnke, D Van Dusschoten, T Aach, ...
Functional Plant Biology 36 (11), 947-959, 2009
Optimale Operatoren in der digitalen Bildverarbeitung
H Scharr
Universitätsbibliothek, 2000
Principles of filter design
B Jähne, H Scharr, S Körkel, B Jähne, H Haußecker, P Geißler
Handbook of computer vision and applications 2, 125-151, 1999
Image analysis: the new bottleneck in plant phenotyping [applications corner]
M Minervini, H Scharr, SA Tsaftaris
IEEE signal processing magazine 32 (4), 126-131, 2015
A stereo imaging system for measuring structural parameters of plant canopies
B Biskup, H Scharr, U Schurr, UWE Rascher
Plant, cell & environment 30 (10), 1299-1308, 2007
Dynamics of seedling growth acclimation towards altered light conditions can be quantified via GROWSCREEN: a setup and procedure designed for rapid optical phenotyping of …
A Walter, H Scharr, F Gilmer, R Zierer, KA Nagel, M Ernst, A Wiese, ...
New Phytologist 174 (2), 447-455, 2007
Machine Learning for Plant Phenotyping Needs Image Processing
SA Tsaftaris, M Minervini, H Scharr
Trends in Plant Science 1481, 2016
Recovery dynamics of growth, photosynthesis and carbohydrate accumulation after de-submergence: a comparison between two wetland plants showing escape and quiescence strategies
FL Luo, KA Nagel, H Scharr, B Zeng, U Schurr, S Matsubara
Annals of Botany 107 (1), 49-63, 2011
Optimal filters for extended optical flow
H Scharr
Complex Motion, 14-29, 2007
Arigan: Synthetic arabidopsis plants using generative adversarial network
M Valerio Giuffrida, H Scharr, SA Tsaftaris
Proceedings of the IEEE international conference on computer vision …, 2017
Channel smoothing: Efficient robust smoothing of low-level signal features
M Felsberg, PE Forssén, H Scharr
IEEE Transactions on Pattern Analysis and Machine Intelligence 28 (2), 209-222, 2005
QTL analysis of early stage heterosis for biomass in Arabidopsis
RC Meyer, B Kusterer, J Lisec, M Steinfath, M Becher, H Scharr, ...
Theoretical and Applied Genetics 120, 227-237, 2010
The leaf angle distribution of natural plant populations: assessing the canopy with a novel software tool
M Müller-Linow, F Pinto-Espinosa, H Scharr, U Rascher
Plant methods 11, 1-16, 2015
HyperART: non-invasive quantification of leaf traits using hyperspectral absorption-reflectance-transmittance imaging
S Bergsträsser, D Fanourakis, S Schmittgen, MP Cendrero-Mateo, ...
Plant methods 11, 1-17, 2015
Annotated image datasets of rosette plants
H Scharr, M Minervini, A Fischbach, SA Tsaftaris
European conference on computer vision. Zürich, Suisse, 6-12, 2014
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