Global Wheat Head Detection Challenges: Winning Models and Application for Head Counting

被引：4

作者：

David, Etienne ^{[1
,2
]}

Ogidi, Franklin ^{[3
]}

Smith, Daniel ^{[4
]}

Chapman, Scott ^{[4
]}

de Solan, Benoit ^{[2
]}

Guo, Wei ^{[5
]}

Baret, Frederic ^{[1
]}

Stavness, Ian ^{[3
]}

机构：

[1] INRA, UMR 1114 EMMAH, Avignon, France

[2] Arvalis Inst Vegetal, Paris, France

[3] Univ Saskatchewan, Dept Comp Sci, Saskatoon, SK, Canada

[4] Univ Queensland, Sch Food & Agr Sci, Brisbane, Australia

[5] Univ Tokyo, Grad Sch Agr & Life Sci, Tokyo, Japan

来源：

PLANT PHENOMICS | 2023年 / 5卷

关键词：

D O I：

10.34133/plantphenomics.0059

中图分类号：

S3 [农学（农艺学）];

学科分类号：

0901 ;

摘要：

Data competitions have become a popular approach to crowdsource new data analysis methods for general and specialized data science problems. Data competitions have a rich history in plant phenotyping, and new outdoor field datasets have the potential to embrace solutions across research and commercial applications. We developed the Global Wheat Challenge as a generalization competition in 2020 and 2021 to find more robust solutions for wheat head detection using field images from different regions. We analyze the winning challenge solutions in terms of their robustness when applied to new datasets. We found that the design of the competition had an influence on the selection of winning solutions and provide recommendations for future competitions to encourage the selection of more robust solutions.

引用

页数：15

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