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What is Food Adulteration Detection Techniques about?
The document reviews various methodologies for food adulteration detection systems utilizing vision-based methods and machine learning techniques. It summarizes the proposed methodologies, datasets used, and conclusions drawn from different studies, highlighting the accuracy and effectiveness of various approaches. Key techniques include image processing, neural networks, and spectral analysis, with notable results in detecting adulteration in products like rice, meat, and dairy.
- Author
- Dude
- Language
- EN