activity
20202022
most citedGlobal Wheat Head Detection (GWHD) dataset: a large and diverse dataset of high resolution RGB labelled images to develop and benchmark wheat head detection methods

19 citations · 44 across the 5 of their papers we have counts for

collaborators

5 papers

eess.SP2022

HERMES: Hybrid Error-corrector Model with inclusion of External Signals for nonstationary fashion time series

Etienne David, Jean Bellot, Sylvain Le Corff

Developing models and algorithms to predict nonstationary time series is a long standing statistical problem. It is crucial for many applications, in particular for fashion or reta…

cs.LG2021★ 12 cited

Extending the WILDS Benchmark for Unsupervised Adaptation

Shiori Sagawa, Pang Wei Koh, Tony Lee +17

Machine learning systems deployed in the wild are often trained on a source distribution but deployed on a different target distribution. Unlabeled data can be a powerful point of…

cs.CV2021★ 10 cited

Global Wheat Head Dataset 2021: more diversity to improve the benchmarking of wheat head localization methods

Etienne David, Mario Serouart, Daniel Smith +32

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…

cs.CV2021★ 3 cited

Global Wheat Challenge 2020: Analysis of the competition design and winning models

Etienne David, Franklin Ogidi, Wei Guo +2

Data competitions have become a popular approach to crowdsource new data analysis methods for general and specialized data science problems. In plant phenotyping, data competitions…

cs.CV2020★ 19 cited

Global Wheat Head Detection (GWHD) dataset: a large and diverse dataset of high resolution RGB labelled images to develop and benchmark wheat head detection methods

E. David, S. Madec, P. Sadeghi-Tehran +14

Detection of wheat heads is an important task allowing to estimate pertinent traits including head population density and head characteristics such as sanitary state, size, maturit…