Machine Learning for Plant Phenotyping Needs Image Processing.

  title={Machine Learning for Plant Phenotyping Needs Image Processing.},
  author={Sotirios A. Tsaftaris and Massimo Minervini and Hanno Scharr},
  journal={Trends in plant science},
  volume={21 12},
Sotirios A. Tsaftaris , Massimo Minervini B and Hanno Scharr C A Institute for Digital Communications, School of Engineering, University of Edinburgh, Edinburgh, EH9 3FG, UK B Pattern Recognition and Image Analysis (PRIAn) IMT School for Advanced Studies, Lucca, 55100, Italy C Institute of Bioand Geosciences: Plant Sciences (IBG-2) Forschungszentrum Jülich GmbH, D-52425, Jülich, Germany * Corresponding author. Email: (S.A. Tsaftaris), URL: 
Highly Cited
This paper has 19 citations. REVIEW CITATIONS
Related Discussions
This paper has been referenced on Twitter 14 times. VIEW TWEETS

From This Paper

Figures, tables, and topics from this paper.

Explore Further: Topics Discussed in This Paper


Publications citing this paper.
Showing 1-10 of 14 extracted citations

Leaves image synthesis using generative adversarial networks with regularization improvement

2018 International Conference on Information and Communications Technology (ICOIACT) • 2018
View 2 Excerpts

ARIGAN: Synthetic Arabidopsis Plants Using Generative Adversarial Network

2017 IEEE International Conference on Computer Vision Workshops (ICCVW) • 2017
View 2 Excerpts

Deep Learning for Multi-task Plant Phenotyping

2017 IEEE International Conference on Computer Vision Workshops (ICCVW) • 2017
View 1 Excerpt


Publications referenced by this paper.
Showing 1-10 of 12 references

2016) Finely-grained annotated datasets for image-based plant phenotyping

M Minervini, A Fischbach, H Scharr, S. A. Tsaftaris
Pattern Recognition Letters • 2016

An opinion on imaging challenges in phenotyping field crops

Machine Vision and Applications • 2015
View 1 Excerpt

Growth Signatures of Rosette Plants from Time-Lapse Video

IEEE/ACM Transactions on Computational Biology and Bioinformatics • 2015

Similar Papers

Loading similar papers…