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

Étienne David | Zendy; Mario Serouart | Zendy; Daniel Smith | Zendy; Simon Madec | Zendy; Kaaviya Velumani | Zendy; Shouyang Liu | Zendy; Xu Wang | Zendy; Francisco Pinto | Zendy; Shahameh Shafiee | Zendy; Izzat S. A. Tahir | Zendy; Hisashi Tsujimoto | Zendy; Shuhei Nasuda | Zendy; Bangyou Zheng | Zendy; Norbert Kirchgeßner | Zendy; Helge Aasen | Zendy; Andreas Hund | Zendy; Pouria SadeghiTehran | Zendy; Koichi Nagasawa | Zendy; Goro Ishikawa | Zendy; Sébastien Dandrifosse | Zendy; Alexis Carlier | Zendy; Benjamin Dumont | Zendy; Benoît Mercatoris | Zendy; Byron Evers | Zendy; Ken Kuroki | Zendy; Haozhou Wang | Zendy; Masanori Ishii | Zendy; Minhajul Arifin Badhon | Zendy; Curtis Pozniak | Zendy; David LeBauer | Zendy; Morten Lillemo | Zendy; Jesse Poland | Zendy; Scott Chapman | Zendy; Benoît de Solan | Zendy; Frédéric Baret | Zendy; Ian Stavness | Zendy; Wei Guo | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

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

Author(s) -

Étienne David,

Mario Serouart,

Daniel Smith,

Simon Madec,

Kaaviya Velumani,

Shouyang Liu,

Xu Wang,

Francisco Pinto,

Shahameh Shafiee,

Izzat S. A. Tahir,

Hisashi Tsujimoto,

Shuhei Nasuda,

Bangyou Zheng,

Norbert Kirchgeßner,

Helge Aasen,

Andreas Hund,

Pouria SadeghiTehran,

Koichi Nagasawa,

Goro Ishikawa,

Sébastien Dandrifosse,

Alexis Carlier,

Benjamin Dumont,

Benoît Mercatoris,

Byron Evers,

Ken Kuroki,

Haozhou Wang,

Masanori Ishii,

Minhajul Arifin Badhon,

Curtis Pozniak,

David LeBauer,

Morten Lillemo,

Jesse Poland,

Scott Chapman,

Benoît de Solan,

Frédéric Baret,

Ian Stavness,

Wei Guo

Publication year - 2021

Publication title -

plant phenomics

Language(s) - English

Resource type - Journals

eISSN - 2097-0374

pISSN - 2643-6515

DOI - 10.34133/2021/9846158

Subject(s) - benchmarking , computer science , reliability (semiconductor) , competition (biology) , head (geology) , rgb color model , artificial intelligence , data science , business , marketing , biology , ecology , paleontology , power (physics) , physics , quantum mechanics

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.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research