mlsanityData to 7 Oct 2026

Global Wheat Challenge 2020: Analysis of the competition design and winning models

arXiv 2105.06182 ↗First posted 13 May 2021cs.CVcited by 1

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Abstract (arXiv)

Data competitions have become a popular approach to crowdsource new data analysis methods for general and specialized data science problems. In plant phenotyping, data competitions have a rich history, and new outdoor field datasets have potential for new data competitions. We developed the Global Wheat Challenge as a generalization competition to see if solutions for wheat head detection from field images would work in different regions around the world. In this paper, we analyze the winning challenge solutions in terms of their robustness and the relative importance of model and data augmentation design decisions. We found that the design of the competition influence the selection of winning solutions and provide recommendations for future competitions in an attempt to garner more robust winning solutions.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 13 of its 35 references that are in the map. First posted on arXiv 13 May 2021.

Builds on

13 of 35 references.

References · 13

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1 more
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Cited by year

Citing papers per year: 2021: 1.

1 paper.

  1. 2021Global Wheat Head Dataset 2021: more diversity to improve the benchmarking of wheat head localization methodscited by 4