Wheat rust is a devastating plant disease that affects many African crops, reducing yields and affecting the livelihoods of farmers and decreasing food security across the continent. The disease is difficult to monitor at a large scale, making it difficult to control and eradicate.
The objective of this challenge is to build a machine learning algorithm to correctly classify if a plant is healthy, has stem rust, or has leaf rust.
An accurate image recognition model that can detect wheat rust from any image will enable a crowd-sourced approach to monitoring African crops, through avenues such as social media and smartphone images. This challenge represents a potential breakthrough in our ability to monitor and control plant diseases like wheat rust that affect African livelihoods.
This competition is sponsored by the Big Data Platform of the CGIAR and for the ICLR conference.
About the Computer Vision for Agriculture (CV4A) Workshop and ICLR (cv4gc.org):
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. The Computer Vision for Agriculture (CV4A) 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. 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.
About The International Conference on Learning Representations (ICLR) (iclr.cc):
ICLR is the premier gathering of professionals dedicated to the advancement of the branch of artificial intelligence called representation learning, but generally referred to as deep learning.
ICLR is globally renowned for presenting and publishing cutting-edge research on all aspects of deep learning used in the fields of artificial intelligence, statistics and data science, as well as important application areas such as machine vision, computational biology, speech recognition, text understanding, gaming, and robotics.
Participants at ICLR span a wide range of backgrounds, from academic and industrial researchers, to entrepreneurs and engineers, to graduate students and postdocs.
About CGIAR (cgiar.org):
The CGIAR (formerly the Consultative Group for International Agricultural Research) is a global partnership engaged in research for a food-secured future. The CGIAR is made up of 15 research centers and operates in dozens of countries across Asia, Africa, and Latin America.