DeepWeeds is the first large-scale public multi-class weed image dataset, allowing the development of powerful classification methods to make robotic weed control feasible. The dataset contains 17,509 labeled images of eight nationally important weed species in Australia.

Citation

@article{DeepWeeds2019,
author = {Alex Olsen and
Dmitry A. Konovalov and
Bronson Philippa and
Peter Ridd and
Jake C. Wood and
Jamie Johns and
Wesley Banks and
Benjamin Girgenti and
Owen Kenny and
James Whinney and
Brendan Calvert and
Mostafa {Rahimi Azghadi} and
Ronald D. White},
title = {{DeepWeeds: A Multiclass Weed Species Image Dataset for Deep Learning}},
journal = {Scientific Reports},
year = 2019,
number = 2058,
month = 2,
volume = 9,
issue = 1,
day = 14,
url = "https://doi.org/10.1038/s41598-018-38343-3",
doi = "10.1038/s41598-018-38343-3"
}