Automated Detection of Adulterated Milk Using Computer Vision and 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 Nairobi, Kenya Chapter.
The problem
Determining adulteration of milk is critical in milk’s demand and supply value chain. However, the current approaches to distinguishing between adulterated milk and adulteration-free milk are constrained by the requirement of human interpretation. In addition, the current methods only measure the presence or lack of adulterants in milk but are limited in measuring the concentration levels of adulterants in the milk being tested.
Milk product has characteristics that can be extracted using computer vision and deep learning technologies and analyzed. These artificial intelligence (AI) techniques have not been widely used in analyzing milk products. An AI solution can help identify adulterated milk from adulteration-free milk with precision.
The goals
In this project, the Omdena Kenya, Nairobi Chapter team aims to develop a computer vision solution that detects the presence of adulterants in milk using features learned from the milk product (Deep Learning).
The project’s chief goal is to build an AI data tool/product for distinguishing adulterated milk from non-adulterated milk.
With a duration of 8-weeks, this project aims to achieve the following:
- Data Collection
- Data Preprocessing
- Feature Extraction
- Model Development and Training
- Model Evaluation
- App 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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