Computer Vision for Automated Food Contamination Detection
This project aims to develop an automated contamination detection system using advanced computer vision technologies in food production environments. High-resolution imaging and deep learning models are applied to identify contamination patterns, foreign materials, and microbial risks in food products. The system is trained using diverse datasets to improve detection accuracy and adaptability across different food […]