title: AI For Detecting Waterborne Diseases through Image Analysis
abstract: The detection of waterborne pathogens is essential for safeguarding public health, especially in regions with limited access to clean and safe water. Traditional methods of microorganism detection often rely on time-consuming and resource-intensive laboratory techniques. To address this, the present study introduces an artificial intelligence-based solution using the YOLOv5 deep learning algorithm to detect and classify microorganisms in water samples. The model is trained on the Environmental M
journal: International Journal of Scientific Research in Computer Science Engineering and Information Technology