Global Wheat Head Dataset 2021: more diversity to improve the benchmarking of wheat head localization methods
The Global Wheat Head Detection (GWHD) dataset was created in 2020 and has assembled 193,634 labelled wheat heads from 4,700 RGB images acquired from various acquisition platforms and 7 countries/institutions. With an associated competition hosted in Kaggle, GWHD has successfully attracted attention...
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Main Authors: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
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Format: | Journal Article |
Language: | English |
Published: |
17-05-2021
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Subjects: | |
Online Access: | Get full text |
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Summary: | The Global Wheat Head Detection (GWHD) dataset was created in 2020 and has
assembled 193,634 labelled wheat heads from 4,700 RGB images acquired from
various acquisition platforms and 7 countries/institutions. With an associated
competition hosted in Kaggle, GWHD has successfully attracted attention from
both the computer vision and agricultural science communities. From this first
experience in 2020, a few avenues for improvements have been identified,
especially from the perspective of data size, head diversity and label
reliability. To address these issues, the 2020 dataset has been reexamined,
relabeled, and augmented by adding 1,722 images from 5 additional countries,
allowing for 81,553 additional wheat heads to be added. We now release a new
version of the Global Wheat Head Detection (GWHD) dataset in 2021, which is
bigger, more diverse, and less noisy than the 2020 version. The GWHD 2021 is
now publicly available at http://www.global-wheat.com/ and a new data challenge
has been organized on AIcrowd to make use of this updated dataset. |
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DOI: | 10.48550/arxiv.2105.07660 |