Related references
Note: Only part of the references are listed.Moderate to severe water limitation differentially affects the phenome and ionome of Arabidopsis
Lucia M. Acosta-Gamboa et al.
FUNCTIONAL PLANT BIOLOGY (2017)
Image Analysis in Plant Sciences: Publish Then Perish
Guillaume Lobet
TRENDS IN PLANT SCIENCE (2017)
Time dependent genetic analysis links field and controlled environment phenotypes in the model C4 grass Setaria
Max J. Feldman et al.
PLOS GENETICS (2017)
Deep Plant Phenomics: A Deep Learning Platform for Complex Plant Phenotyping Tasks
Jordan R. Ubbens et al.
FRONTIERS IN PLANT SCIENCE (2017)
Deep machine learning provides state-of-the-art performance in image-based plant phenotyping
Michael P. Pound et al.
GIGASCIENCE (2017)
Combining semi-automated image analysis techniques with machine learning algorithms to accelerate large-scale genetic studies
Jonathan A. Atkinson et al.
GIGASCIENCE (2017)
Leaf segmentation in plant phenotyping: a collation study
Hanno Scharr et al.
MACHINE VISION AND APPLICATIONS (2016)
Measures for interoperability of phenotypic data: minimum information requirements and formatting
Hanna Cwiek-Kupczynska et al.
PLANT METHODS (2016)
The Quest for Understanding Phenotypic Variation via Integrated Approaches in the Field Environment
Duke Pauli et al.
PLANT PHYSIOLOGY (2016)
Machine Learning for High-Throughput Stress Phenotyping in Plants
Arti Singh et al.
TRENDS IN PLANT SCIENCE (2016)
Ten Simple Rules for Taking Advantage of Git and GitHub
Yasset Perez-Riverol et al.
PLOS COMPUTATIONAL BIOLOGY (2016)
Lights, camera, action: high-throughput plant phenotyping is ready for a close-up
Noah Fahlgren et al.
CURRENT OPINION IN PLANT BIOLOGY (2015)
A Versatile Phenotyping System and Analytics Platform Reveals Diverse Temporal Responses to Water Availability in Setaria
Noah Fahlgren et al.
MOLECULAR PLANT (2015)
Image-based plant phenotyping with incremental learning and active contours
Massimo Minervini et al.
ECOLOGICAL INFORMATICS (2014)
Euclidean Distance Geometry and Applications
Leo Liberti et al.
SIAM REVIEW (2014)
Best Practices for Scientific Computing
Greg Wilson et al.
PLOS BIOLOGY (2014)
scikit-image: image processing in Python
Stefan van der Walt et al.
PEERJ (2014)
An online database for plant image analysis software tools
Guillaume Lobet et al.
PLANT METHODS (2013)
Semilandmarks: a method for quantifying curves and surfaces
Philipp Gunz et al.
HYSTRIX-ITALIAN JOURNAL OF MAMMALOGY (2013)
NIH Image to ImageJ: 25 years of image analysis
Caroline A. Schneider et al.
NATURE METHODS (2012)
Python for Scientists and Engineers
K. Jarrod Millman et al.
COMPUTING IN SCIENCE & ENGINEERING (2011)
The NumPy Array: A Structure for Efficient Numerical Computation
Stefan van der Walt et al.
COMPUTING IN SCIENCE & ENGINEERING (2011)
Phenomics - technologies to relieve the phenotyping bottleneck
Robert T. Furbank et al.
TRENDS IN PLANT SCIENCE (2011)
A Quick Guide for Developing Effective Bioinformatics Programming Skills
Joel T. Dudley et al.
PLOS COMPUTATIONAL BIOLOGY (2009)
Python for scientific computing
Travis E. Oliphant
COMPUTING IN SCIENCE & ENGINEERING (2007)