Back to Search Start Over

Global Wheat Head Detection 2021: An Improved Dataset for Benchmarking Wheat Head Detection Methods

Authors :
Byron Evers
Alexis Carlier
Izzat S. A. Tahir
David Shaner LeBauer
Pouria Sadhegi-Tehran
Shahameh Shafiee
Bangyou Zheng
Ken Kuroki
Goro Ishikawa
Francisco de Assis de Carvalho Pinto
Benoit de Solan
Haozhou Wang
Scott Chapman
Hisashi Tsujimoto
Sébastien Dandrifosse
Minhajul A. Badhon
Etienne David
Koichi Nagasawa
Ian Stavness
Frédéric Baret
Wei Guo
Mario Serouart
Curtis J. Pozniak
Daniel J. Smith
Kaaviya Velumani
Norbert Kirchgessner
Xu Wang
Masanori Ishii
Morten Lillemo
Shuhei Nasuda
Andreas Hund
Helge Aasen
Shouyang Liu
Benjamin Dumont
Simon Madec
Benoît Mercatoris
Jesse Poland
Source :
Plant Phenomics, Plant Phenomics, Vol 2021 (2021), Plant Phenomics, 2021
Publisher :
American Association for the Advancement of Science (AAAS)

Abstract

The Global Wheat Head Detection (GWHD) dataset was created in 2020 and has assembled 193,634 labelled wheat heads from 4700 RGB images acquired from various acquisition platforms and 7 countries/institutions. With an associated competition hosted in Kaggle, GWHD_2020 has successfully attracted attention from both the computer vision and agricultural science communities. From this first experience, a few avenues for improvements have been identified regarding data size, head diversity, and label reliability. To address these issues, the 2020 dataset has been reexamined, relabeled, and complemented by adding 1722 images from 5 additional countries, allowing for 81,553 additional wheat heads. We now release in 2021 a new version of the Global Wheat Head Detection dataset, which is bigger, more diverse, and less noisy than the GWHD_2020 version.<br />Plant Phenomics, 2021

Details

Database :
OpenAIRE
Journal :
Plant Phenomics, Plant Phenomics, Vol 2021 (2021), Plant Phenomics, 2021
Accession number :
edsair.doi.dedup.....5057b1a2e382f53a08bdfd1bb6182375