Connectionists: CFP: Computer Vision for Agriculture (CV4A) Workshop at ICLR 2020

[Laura Sevilla]

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CALL FOR PAPERS
ICLR 2020 Workshop on Computer Vision for Agriculture (CV4A)
April 26 2020, Addis Ababa, Ethiopia
Conference Website: https://www.cv4gc.org/cv4a2020
 -- In conjunction with the International Conference on Representation
Learning (ICLR) 2020

IMPORTANT DATES
Paper submission deadline     : February 14, 2020
Notification of acceptance       : February 25, 2020
Workshop                                : April 26, 2020
Challenge close                       : Mid-March 2020
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Artificial intelligence has invaded the agriculture field during the last
few years. From automatic crop monitoring via drones, smart agricultural
equipment, food security and camera-powered apps assisting farmers to
satellite imagery based global crop disease prediction and tracking,
computer vision has been a ubiquitous tool. This workshop aims to expose
the fascinating progress and unsolved problems of computational agriculture
to the AI research community. It is jointly organized by AI and
computational agriculture researchers and has the support of CGIAR, a
global partnership that unites international organizations engaged in
agricultural research for a food-secure future.
Computer Vision for Agriculture (CV4A) is the second workshop of the
Computer Vision for Global Challenges initiative and will focus on
agriculture. It will be held in April 2020, in conjunction with the
International Conference on Representation Learning (ICLR), in Addis Ababa,
Ethiopia. It will be a full-day event and will feature invited speakers,
poster and spotlight presentations, a panel discussion and (tentatively) a
mentoring/networking dinner.

CHALLENGES AND COMPETITIONS
CV4A will feature two open challenges, both hosted on the African platform
Zindi <https://zindi.africa/>:
* The CGIAR Wheat Rust Detection Challenge
<https://zindi.africa/competitions/iclr-workshop-challenge-1-cgiar-computer-vision-for-crop-disease>
* The Radiant Earth Foundation Crop Classification using Earth Observations
Challenge
<https://zindi.africa/competitions/iclr-workshop-challenge-2-radiant-earth-computer-vision-for-crop-recognition>
Both challenges will feature *cash prizes and travel grants for the top
performing submission*, as well as the top performing submission from an
African researcher and the top performing submission from a
female-identified African researcher. More details coming soon!


CALL FOR PAPERS
We invite researchers to submit their recent work on Computer Vision
applications, tasks and challenges inspired by and applied to agriculture,
with a special focus on developing regions. Topic include but are not
limited to:

 - Crop health (pests, diseases, plant nutrient deficiencies) and crop
yield estimation.
 - Crop type recognition from ground and/or satellite imagery. Such data
can be used to target interven- tions, assess risk, evaluate the impact of
programs.
 - Artificial intelligence for bottom-up, farmer-led crop improvement.
 - Hyper-spectral (e.g. NIR, MIR, x-ray fluorescence) imaging for detecting
early-stage or physiological issues in crops (e.g. photosynthetic activity,
water stress, nutrient stress).
 - Whole-field, multi-view crop diagnostics.
 - Computer vision methods for food security, index insurance,
drought/flood early warning systems.
 - Multi-modal integration of data from diverse sensors.
 - Crowdsourcing agricultural data.
 - Papers will be presented as poster and oral presentations. There
will be *some
travel support* to presenters.

Researchers based in developing regions are strongly encouraged to submit


PAPER SUBMISSION
Up to four pages papers in PDF format, with unlimited pages for references.
To prepare your submission to the CV4A workshop, please use the ICLR 2020
LaTex style files. The review process is double-blind.

Submissions will be handled via CMT:
https://cmt3.research.microsoft.com/CV4A2020


PEOPLE
 - Workshop organizers
Yannis Kalantidis (Naver Labs Europe)
Laura Sevilla-Lara (University of Edinburgh)
Ernest Mwebaze (Google AI Ghana)
Dina Machuve (Nelson Mandela African Institution of Science and Technology)

 - Challenge Organizers
Hamed Alemohammad (Radiant Earth Foundation)
David Guerena (CIMMYT)

- Essential Collaborators
Drew Westbury (Facebook)
Celina Lee (Zindi)
Jamie Yang (Facebook)
Brian King (CGIAR Platform for Big Data in Agriculture)
Lorenzo Torresani (Facebook AI and Dartmouth)
Timnit Gebru (Google AI)
John Quinn (Makerere University & Google AI Ghana)
Larry Zitnick (University of Washington & Facebook AI)
Jitendra Malik (UC Berkeley & Facebook AI)
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