19 citations · 29 across the 5 of their papers we have counts for
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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…
AutoCount: Unsupervised Segmentation and Counting of Organs in Field Images
Jordan Ubbens, Tewodros Ayalew, Steve Shirtliffe +3
Counting plant organs such as heads or tassels from outdoor imagery is a popular benchmark computer vision task in plant phenotyping, which has been previously investigated in the…
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…
Crop Lodging Prediction from UAV-Acquired Images of Wheat and Canola using a DCNN Augmented with Handcrafted Texture Features
Sara Mardanisamani, Farhad Maleki, Sara Hosseinzadeh Kassani +12
Lodging, the permanent bending over of food crops, leads to poor plant growth and development. Consequently, lodging results in reduced crop quality, lowers crop yield, and makes h…
DeepWheat: Estimating Phenotypic Traits from Crop Images with Deep Learning
Shubhra Aich, Anique Josuttes, Ilya Ovsyannikov +6
In this paper, we investigate estimating emergence and biomass traits from color images and elevation maps of wheat field plots. We employ a state-of-the-art deconvolutional networ…