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A deep learning-based approach for high-throughput hypocotyl phenotyping
Orsolya Dobos, Peter Horvath, Ferenc Nagy, Tivadar Danka, András Viczián
doi: https://doi.org/10.1101/651729
Orsolya Dobos
1Institute of Plant Biology, Biological Research Centre of the Hungarian Academy of Sciences, Temesvári krt. 62, H-6726 Szeged, Hungary
2Doctoral School in Biology, Faculty of Science and Informatics, University of Szeged, Szeged, H-6726, Hungary
Peter Horvath
3Institute of Biochemistry, Biological Research Centre of the Hungarian Academy of Sciences, Temesvári krt. 62, H-6726 Szeged, Hungary
Ferenc Nagy
1Institute of Plant Biology, Biological Research Centre of the Hungarian Academy of Sciences, Temesvári krt. 62, H-6726 Szeged, Hungary
Tivadar Danka
3Institute of Biochemistry, Biological Research Centre of the Hungarian Academy of Sciences, Temesvári krt. 62, H-6726 Szeged, Hungary
András Viczián
1Institute of Plant Biology, Biological Research Centre of the Hungarian Academy of Sciences, Temesvári krt. 62, H-6726 Szeged, Hungary
Posted May 27, 2019.
A deep learning-based approach for high-throughput hypocotyl phenotyping
Orsolya Dobos, Peter Horvath, Ferenc Nagy, Tivadar Danka, András Viczián
bioRxiv 651729; doi: https://doi.org/10.1101/651729
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