期刊
TRENDS IN PLANT SCIENCE
卷 24, 期 2, 页码 99-102出版社
ELSEVIER SCIENCE LONDON
DOI: 10.1016/j.tplants.2018.10.016
关键词
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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 dataset 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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