David Etienne, Serouart Mario, Smith Daniel, Madec Simon, Velumani Kaaviya, Liu Shouyang, Wang Xu, Pinto Francisco, Shafiee Shahameh, Tahir Izzat S A, Tsujimoto Hisashi, Nasuda Shuhei, Zheng Bangyou, Kirchgessner Norbert, Aasen Helge, Hund Andreas, Sadhegi-Tehran Pouria, Nagasawa Koichi, Ishikawa Goro, Dandrifosse Sébastien, Carlier Alexis, Dumont Benjamin, Mercatoris Benoit, Evers Byron, Kuroki Ken, Wang Haozhou, Ishii Masanori, Badhon Minhajul A, Pozniak Curtis, LeBauer David Shaner, Lillemo Morten, Poland Jesse, Chapman Scott, de Solan Benoit, Baret Frédéric, Stavness Ian, Guo Wei
Arvalis, Institut du Végétal, 3 Rue Joseph et Marie Hackin, 75116 Paris, France.
UMR1114 EMMAH, INRAE, Centre PACA, Bâtiment Climat, Domaine Saint-Paul, 228 Route de l'Aérodrome, CS 40509, 84914 Avignon Cedex, France.
Plant Phenomics. 2021 Sep 22;2021:9846158. doi: 10.34133/2021/9846158. eCollection 2021.
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.
全球小麦穗检测（GWHD）数据集于2020年创建，它汇集了从7个国家/机构的各种采集平台获取的4700张RGB图像中的193,634个带标签的小麦穗。通过在Kaggle上举办的相关竞赛，GWHD_2020成功吸引了计算机视觉和农业科学界的关注。从这第一次经验中，已经确定了在数据规模、穗的多样性和标签可靠性方面的一些改进途径。为了解决这些问题，对2020年的数据集进行了重新检查、重新标记，并通过添加来自另外5个国家的1722张图像进行补充，从而增加了81,553个小麦穗。我们现在于2021年发布了全球小麦穗检测数据集的新版本，它比GWHD_2020版本更大、更多样化且噪声更少。
