Leaf Disease Classification Using Deep Learning

This Omdena Local Chapter Challenge runs for 8 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 Addis Ababa, Ethiopia Chapter.
The problem
These days, many researchers are conducting research and applying deep learning technologies to different plant disease detection problems. Faba Bean diseases are the major challenges for crop producers which causes a huge loss in both quality and quantity. Analyzing the symptoms seen on the leaves of the plant and recognizing the disease plays a key role in the successful cultivation of crops. A proper diagnosis mechanism is an extremely important task in preventing the disease in its early stages. Proper identification of diseases and taking immediate control measures are the most important aspects of plant pathology.
To our best knowledge, no automated Faba Bean disease detection system is designed either using traditional machine learning or deep learning techniques. Even though many crop disease detection systems are developed applying those systems for Faba Bean disease detection is not feasible. This is because the disease features such as color and texture are different from crop to crop. Therefore, we decided to develop a Faba Bean crop leaf disease detection system by applying a deep learning technique called CNN.
The goals
- Data Collection and Exploratory Data Analysis
- Preprocessing
- Feature Extraction
- Model Development and Training
- Evaluate Model
- Prototype development
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.
First Omdena Local Chapter Challenge?
Beginner-friendly, but also welcomes experts
Education-focused
Open-source
Duration: 4 to 8 weeks
Your Benefits
Address a significant real-world problem with your skills
Build your project portfolio
Access paid projects (as an Omdena Top Talent)
Get hired at top organizations
Requirements
Good English
Suitable for AI/ Data Science beginners but also more senior collaborators
Learning mindset
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