Vitamins Deficiency Detection Using Deep Learning and Image Processing

An innovative solution has been developed to help individuals identify potential nutrient deficiencies without the need for invasive blood tests.This application utilizes deep learning-based Convolutional Neural Network (CNN) algorithms to analyze photographs of the eyes, lips, tongue, and nails for outward signs of deficiencies.The process begins with preprocessing the dataset, followed by training the CNN model using the collected data.Once the model is trained, it is saved for future use, and testing is carried out using OpenCV.This approach allows for efficient and non-invasive screening for nutrient deficiencies, aiding in early detection and intervention.