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The paper "Detection of Nutrition Information Using AI" aims to simplify accessing nutrition information about fruits using images. Designed with Python as the front end and MySQL server as the back end, it addresses the tedious process of manually searching for nutrition details like carbohydrates, proteins, fats, vitamins, and fiber. The application uses the YOLO object detection algorithm to automatically identify fruits from user-uploaded images. Once the fruit is detected, the system retrieves its nutritional information from a database, providing users with comprehensive details and recommended quantities. This user-friendly application makes it easy to quickly obtain accurate nutrition information.
Keywords:
Nutrition, Detection, AI, Yolo
Cite Article:
"Detection of Nutrition Information using AI ", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.9, Issue 9, page no.188 - 193, September-2024, Available :http://www.ijrti.org/papers/IJRTI2409027.pdf
Downloads:
000204859
ISSN:
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator