The automatic segmentation of ears in wheat canopy images is an important step to measure ear density or extract relevant plant traits separately for the different organs.Recent deep learning algorithms appear as prom...The automatic segmentation of ears in wheat canopy images is an important step to measure ear density or extract relevant plant traits separately for the different organs.Recent deep learning algorithms appear as promising tools to accurately detect ears in a wide diversity of conditions.However,they remain complicated to implement and necessitate a huge training database.This paper is aimed at proposing an easy and quick to train and robust alternative to segment wheat ears from heading to maturity growth stage.展开更多
文摘The automatic segmentation of ears in wheat canopy images is an important step to measure ear density or extract relevant plant traits separately for the different organs.Recent deep learning algorithms appear as promising tools to accurately detect ears in a wide diversity of conditions.However,they remain complicated to implement and necessitate a huge training database.This paper is aimed at proposing an easy and quick to train and robust alternative to segment wheat ears from heading to maturity growth stage.
