Meet the winners of ICLR Workshop Challenge #1: CGIAR Computer Vision for Crop Disease

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.

Teams and collaboration

You may participate in this competition as an individual or in a team of up to four people. When creating a team, the team must have a total submission count less than or equal to the maximum allowable submissions as of the formation date. A team will be allowed the maximum number of submissions for the competition, minus the highest number of submissions among team members at team formation. Prizes are transferred only to the individual players or to the team leader.

Multiple accounts per user are not permitted, and neither is collaboration or membership across multiple teams. Individuals and their submissions originating from multiple accounts will be disqualified.

Code must not be shared privately outside of a team. Any code that is shared, must be made available to all competition participants through the platform. (i.e. on the discussion boards).

Datasets and packages

The solution must use publicly-available, open-source packages only. Your models should not use any of the metadata provided.

You may use only the datasets provided for this competition.

The data used in this competition is the sole property of Zindi and the competition host. You may not transmit, duplicate, publish, redistribute or otherwise provide or make available any competition data to any party not participating in the Competition (this includes uploading the data to any public site such as Kaggle or GitHub). You may upload, store and work with the data on any cloud platform such as Google Colab, AWS or similar, as long as 1) the data remains private and 2) doing so does not contravene Zindi’s rules of use.

You must notify Zindi immediately upon learning of any unauthorised transmission of or unauthorised access to the competition data, and work with Zindi to rectify any unauthorised transmission or access.

Your solution must not infringe the rights of any third party and you must be legally entitled to assign ownership of all rights of copyright in and to the winning solution code to Zindi.

Submissions and winning

You may make a maximum of 10 submissions per day. Your highest-scoring solution on the private leaderboard at the end of the competition will be the one by which you are judged.

As the challenge has now closed, the maximum number of submissions per day is 30.

Zindi maintains a public leaderboard and a private leaderboard for each competition. The Public Leaderboard includes approximately 20% of the test dataset. While the competition is open, the Public Leaderboard will rank the submitted solutions by the accuracy score they achieve. Upon close of the competition, the Private Leaderboard, which covers 100% of the test dataset, will be made public and will constitute the final ranking for the competition.

If you are in the top 20 at the time the leaderboard closes, we will email you to request your code. On receipt of email, you will have 48 hours to respond and submit your code following the submission guidelines detailed below. Failure to respond will result in disqualification.

If your solution places 1st, 2nd, or 3rd on the final leaderboard, you will be required to submit your winning solution code to us for verification, and you thereby agree to assign all worldwide rights of copyright in and to such winning solution to Zindi.

If two solutions earn identical scores on the leaderboard, the tiebreaker will be the date and time in which the submission was made (the earlier solution will win).

The winners will be paid via bank transfer, PayPal, or other international money transfer platform. International transfer fees will be deducted from the total prize amount, unless the prize money is under $500, in which case the international transfer fees will be covered by Zindi. In all cases, the winners are responsible for any other fees applied by their own bank or other institution for receiving the prize money. All taxes imposed on prizes are the sole responsibility of the winners.

You acknowledge and agree that Zindi may, without any obligation to do so, remove or disqualify an individual, team, or account if Zindi believes that such individual, team, or account is in violation of these rules. Entry into this competition constitutes your acceptance of these official competition rules.

Please refer to the FAQs and Terms of Use for additional rules that may apply to this competition. We reserve the right to update these rules at any time.

Reproducibility

• If your submitted code does not reproduce your score on the leaderboard, we reserve the right to adjust your rank to the score generated by the code you submitted.
• If your code does not run you will be dropped from the top 10. Please make sure your code runs before submitting your solution.
• Always set the seed. Rerunning your model should always place you at the same position on the leaderboard. When running your solution, if randomness shifts you down the leaderboard we reserve the right to adjust your rank to the closest score that your submission reproduces.
• We expect full documentation. This includes:

- All data used

- Output data and where they are stored

- Explanation of features used

- Your solution must include the original data provided by Zindi and validated external data (no processed data)

- All editing of data must be done in a notebook (i.e. not manually in Excel)

Data standards:

• Your submitted code must run on the original train, test, and other datasets provided.
• If external data is allowed it must not exceed 1 GB. External data must be freely and publicly available, including pre-trained models with standard libraries. If external data is allowed, any data used should be shared on the discussion forum.
• Packages:

- You must use the most recent versions of packages. Custom packages in your submission notebook will not be accepted.

- You may only use tools available to everyone i.e. no paid services or free trials that require a credit card.

Consequences of breaking any rules of the competition or submission guidelines:

• First offence: No prizes or points for 6 months. If you are caught cheating all individuals involved in cheating will be disqualified from the challenge(s) you were caught in and you will be disqualified from winning any competitions or Zindi points for the next six months.
• Second offence: Banned from the platform. If you are caught for a second time your Zindi account will be disabled and you will be disqualified from winning any competitions or Zindi points using any other account.

Monitoring of submissions

• We will review the top 20 solutions of every competition when the competition ends.
• We reserve the right to request code from any user at any time during a challenge. You will have 24 hours to submit your code following the rules for code review (see above).
• If you do not submit your code within 24 hours you will be disqualified from winning any competitions or Zindi points for the next six months. If you fall under suspicion again and your code is requested and you fail to submit your code within 24 hours, your Zindi account will be disabled and you will be disqualified from winning any competitions or Zindi points.

Further updates and rulings of note:

• Multiple accounts per user, collaboration or membership across multiple teams are not allowed.
• Code may not be shared privately. Any code that is shared, must be made available to all competition participants through the platform.
• Solutions must use publicly-available, open-source packages only, and all packages must be the most updated versions.
• Solutions must not infringe the rights of any third party and you must be legally entitled to assign ownership of all rights of copyright in and to the winning solution code to Zindi.
• You will be disqualified if you do not respond within the timeframe given in the request for code.

We reserve the right to update these rules at any time.

The evaluation metric for this challenge is Log Loss.

Some images may contain both stem and leaf rust, there is always one type of rust that is more dominant than the other, i.e. you will not find images where both appear equally. The goal is to classify the image according to the type of wheat rust that appears most prominently in the image.

The values can be between 0 and 1, inclusive.

ID       leaf_rust   stem_rust   healthy_wheat   
GVRCWM      0.63       0.98          0.21      
8NRRD6      0.76       0.11          0.56

There are FIVE winners for this competition. Each winner will be invited to take part in the CV4A workshop at ICLR, taking place online 26 April 2020.

1. 1st place overall from any country: An invitation to ICLR plus $1 500 USD.
2. 1st place African citizen currently residing in Africa: An invitation to ICLR plus $1 000 USD.
3. The 1st place female-identified African citizen currently residing in Africa: An invitation to ICLR plus $1 000 USD.
4. 2nd place overall from any country: An invitation to ICLR plus $1 000 USD.
5. 3rd place overall from any country: An invitation to ICLR plus $500 USD.

Additional conditions to note:

• The female-identified African prize will be selected first; the African citizen prize will be selected second; the 'overall' prizes will go to the next highest placed winners.
• If a winner is not able to attend ICLR or accept the prize, we reserve the right to assign the prize to another top person or team on the leaderboard.
• If you are working in a team and your team wins, you will need to immediately notify Zindi who will represent the team at ICLR.
• If a team is composed of both (female) African and non-African data scientists, then your team's category will be determined by the gender and nationality of the person you put forward to represent the team at ICLR.

Competition closes on 29 March 2020.

Final submissions must be received by 11:59 PM GMT.

We reserve the right to update the contest timeline if necessary.