Identifying Corn Diseases from a Picture of Corn Using Computer Vision

This Omdena Local Chapter Challenge runs for 4 weeks and is a unique experience to try and grow your skills in a collaborative and safe environment with a diverse mix of people from all over the world. 

You will work on solving a local problem, initiated by Ethiopia Local Chapter.

The problem

Diseases in corn crops have been a longstanding issue in the agriculture industry, seriously affecting the yield and influencing the economy on a local and international level. These diseases have devastating effects on food production, causing ill effects on farmers’ livelihoods, economic development, and ultimately, food and security. Crops affected by diseases can lose as much as 40% of their yield. The problem extends to every part of the world, and it is not isolated to large commercial farms, as it also affects small-scale farmers, urban growers, and even those who tend to a kitchen garden. The effects of diseases on crops have the potential to affect food prices, which can lead to reduced availability of a critical source of nutrition for many people. Food security is not only a concern for farmers, but also for governments, industries, and institutions that rely on the vital yields of crops. Early detection is vital as it can substantially reduce disease-induced crop losses. Current techniques for diagnosis have relied on manual inspection and have several limitations including high costs, low efficiency, and limited accuracy. Furthermore, the symptoms of different diseases may also overlap, further complicating accurate diagnosis. With the increase in technological advancements, it is vital to embrace these innovations to provide fast and accurate detection and effectively address the impact of diseases on crops.

The goals

• Early Detection of Corn Diseases: To develop a machine learning model that supports early and accurate detection of corn diseases, allowing growers to take real-time, data-driven actions. This can significantly reduce the damage caused by diseases and increase crop yield.
• Better Disease Management: To provide a tool for farmers and growers that helps them to identify systemic and localized patterns of disease, allowing them to undertake better management of the diseases on their farms, including prevention and treatment.

Why join? The uniqueness of Omdena Local Chapter Challenges

Omdena Local Chapter Challenges are not a competition or hackathon but a real-world project that will grow your experience to a new level.

A unique learning experience with the potential to make an impact through the outcome of the project. You will go through an entire data science project lifecycle. This covers problem scoping, data collection, and preparation, as well as modeling for deployment.

And the best part is that you will join the global and collaborative community of Omdena with tons of benefits to accelerate your career.

Read more on how Omdena´s Local Chapters work