Image Processing Based Proposed System for Malnutrition Using Deep Learning
In many nations, malnutrition is the primary cause of death for children under five. An inventive way to handle the problem of hunger in a non-invasive and effective way is through the use of deep learning in image processing for malnutrition diagnosis. The system trains a deep learning model, such as a convolutional neural network, on a huge dataset of photographs of people with various degrees of malnutrition in order to find patterns and features in the photos that indicate malnutritionFor ease of usage by medical practitioners, the trained model is then made available on a web-based platform or mobile device. The suggested system may supplement current practices and offer more data for a thorough evaluation, especially in environments with limited resources.
Authors
- A. Mary Posonia
- Hariom Priyadarshi
- Jai Adithya B
Institutions
- Sathyabama Institute of Science and Technology (IN)
Publication Details
- Published
- 2024-08-08
- DOI
- https://doi.org/10.1109/iccpct61902.2024.10673294
- Primary Topic
- Child Nutrition and Water Access
- Type
- article
- Field-Weighted Citation Impact
- 0.00