Global Wheat Head Detection Challenges: Winning Models and Application for Head Counting
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 commerci...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
American Association for the Advancement of Science (AAAS)
2023-01-01
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| Series: | Plant Phenomics |
| Online Access: | https://spj.science.org/doi/10.34133/plantphenomics.0059 |
| _version_ | 1797794811404615680 |
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| author | Etienne David Franklin Ogidi Daniel Smith Scott Chapman Benoit de Solan Wei Guo Frederic Baret Ian Stavness |
| author_facet | Etienne David Franklin Ogidi Daniel Smith Scott Chapman Benoit de Solan Wei Guo Frederic Baret Ian Stavness |
| author_sort | Etienne David |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-13T03:08:26Z |
| format | Article |
| id | doaj.art-0c1fc606ae874d47997060bf0571fa5a |
| institution | Directory Open Access Journal |
| issn | 2643-6515 |
| language | English |
| last_indexed | 2024-03-13T03:08:26Z |
| publishDate | 2023-01-01 |
| publisher | American Association for the Advancement of Science (AAAS) |
| record_format | Article |
| series | Plant Phenomics |
| spelling | doaj.art-0c1fc606ae874d47997060bf0571fa5a2023-06-26T16:18:47ZengAmerican Association for the Advancement of Science (AAAS)Plant Phenomics2643-65152023-01-01510.34133/plantphenomics.0059Global Wheat Head Detection Challenges: Winning Models and Application for Head CountingEtienne David0Franklin Ogidi1Daniel Smith2Scott Chapman3Benoit de Solan4Wei Guo5Frederic Baret6Ian Stavness7UMR 1114 EMMAH, INRAE, Avignon, France.Department of Computer Science, University of Saskatchewan, Saskatoon, Canada.School of Food and Agricultural Sciences, University of Queensland, Brisbane, Australia.School of Food and Agricultural Sciences, University of Queensland, Brisbane, Australia.Arvalis – Institut du Végétal, Paris, France.Graduate School of Agricultural and Life Sciences, The University of Tokyo, Tokyo, Japan.UMR 1114 EMMAH, INRAE, Avignon, France.Department of Computer Science, University of Saskatchewan, Saskatoon, Canada.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.https://spj.science.org/doi/10.34133/plantphenomics.0059 |
| spellingShingle | Etienne David Franklin Ogidi Daniel Smith Scott Chapman Benoit de Solan Wei Guo Frederic Baret Ian Stavness Global Wheat Head Detection Challenges: Winning Models and Application for Head Counting Plant Phenomics |
| title | Global Wheat Head Detection Challenges: Winning Models and Application for Head Counting |
| title_full | Global Wheat Head Detection Challenges: Winning Models and Application for Head Counting |
| title_fullStr | Global Wheat Head Detection Challenges: Winning Models and Application for Head Counting |
| title_full_unstemmed | Global Wheat Head Detection Challenges: Winning Models and Application for Head Counting |
| title_short | Global Wheat Head Detection Challenges: Winning Models and Application for Head Counting |
| title_sort | global wheat head detection challenges winning models and application for head counting |
| url | https://spj.science.org/doi/10.34133/plantphenomics.0059 |
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