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The 1st Agriculture-Vision Challenge: Methods and Results

Title
The 1st Agriculture-Vision Challenge: Methods and Results
Authors
Chiu, Mang TikXu, XingqianWang, KaiHobbs, JenniferHovakimyan, NairaHuang, Thomas S.Shi, HonghuiWei, YunchaoHuang, ZilongSchwing, AlexanderBrunner, RobertDozier, IvanDozier, WyattGhandilyan, KarenWilson, DavidPark, HyunseongKim, JunheeKim, SunghoLiu, QinghuiKampffmeyer, Michael C.Jenssen, RobertSalberg, Arnt B.Barbosa, AlexandreTrevisan, RodrigoZhao, BingchenYu, ShaozuoYang, SiweiWang, YinSheng, HaoChen, XiaoSu, JingyiRajagopal, RamNg, AndrewHuynh, Van ThongKim, Soo-HyungNa, In-SeopBaid, UjjwalInnani, ShubhamDutande, PrasadBaheti, BhaktiTalbar, SanjayTang, Jianyu
Issue Date
2020-06-16
Citation
2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2020, 212-218
Type
Conference
ISBN
9781728193601
ISSN
2160-7508
Abstract
The first Agriculture-Vision Challenge aims to encourage research in developing novel and effective algorithms for agricultural pattern recognition from aerial images, especially for the semantic segmentation task associated with our challenge dataset. Around 57 participating teams from various countries compete to achieve state-of-the-art in aerial agriculture semantic segmentation. The Agriculture- Vision Challenge Dataset was employed, which comprises of 21, 061 aerial and multi-spectral farmland images. This paper provides a summary of notable methods and results in the challenge. Our submission server and leaderboard will continue to open for researchers that are interested in this challenge dataset and task; the link can be found \color{OrangeRed}{here}. © 2020 IEEE.
URI
http://hdl.handle.net/20.500.11750/12904
DOI
10.1109/CVPRW50498.2020.00032
Publisher
IEEE Computer Society
Files:
There are no files associated with this item.
Collection:
ETC2. Conference Papers


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