Journal Article

FZJ-2019-00723

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Sharing the Right Data Right: A Symbiosis with Machine Learning

Tsaftaris, S. A. (Corresponding author)Extern* ; Scharr, H. (Corresponding author)FZJ*

2019
Elsevier Science Amsterdam [u.a.]

This record in other databases:      

Please use a persistent id in citations: http://hdl.handle.net/2128/23627  doi:10.1016/j.tplants.2018.10.016

Abstract: In 2014 plant phenotyping research was not benefiting from the machine learning (ML) revolution because appropriate data were lacking. We report the success of the first open-access data-set suitable for ML in image-based plant phenotyping suitable for machine learning, fuelling a true interdisciplinary symbiosis, increased awareness, and steep performance improvements on key phenotyping tasks.

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Contributing Institute(s):

1. Pflanzenwissenschaften (IBG-2)

Research Program(s):

1. 583 - Innovative Synergisms (POF3-583) (POF3-583)

Appears in the scientific report 2019

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Database coverage:
; ; BIOSIS Previews ; BIOSIS Reviews Reports And Meetings ; Clarivate Analytics Master Journal List ; Current Contents - Agriculture, Biology and Environmental Sciences ; Current Contents - Life Sciences ; Ebsco Academic Search ; IF >= 10 ; JCR ; NCBI Molecular Biology Database ; Nationallizenz ; SCOPUS ; Science Citation Index ; Science Citation Index Expanded ; Web of Science Core Collection

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