Vitamin Deficiency Detection Using CNN & Image Processing

VITAMIN DEFICIENCY DETECTION USING IMAGE PROCESSING AND CONVOLUTION NEURAL NETWORK

Category: Java Projects

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Vitamin deficiency can lead to various health issues, and early detection is crucial for timely intervention. This study presents a novel approach to detecting vitamin deficiencies through image processing techniques combined with a Convolutional Neural Network (CNN). The proposed system consists of a user-friendly frontend interface that allows users to upload facial and skin images, which are then analyzed to identify visual cues associated with deficiencies of essential vitamins such as A, B, C, and D.
Using a dataset of medical images, the CNN model is trained to recognize specific patterns indicative of vitamin deficiencies, such as skin discoloration, eye abnormalities, and other visible symptoms. Advanced image processing techniques are used to read, enhance, and segment the uploaded images, enabling the CNN to classify the deficiencies with high accuracy.

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VITAMIN DEFICIENCY DETECTION USING IMAGE PROCESSING AND CONVOLUTION NEURAL NETWORK

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