Nutrivision: A CNN-based Mobile Application for Food Classification and Analysis
Year: 2025
Type: article
Abstract: With the increasing awareness of health and nutrition, demand for intelligent systems that provide the appropriate dietary advice is growing. NutriVision is a mobile application on the basis of Convolutional Neural Networks (CNN) for real-time fruit, vegetable, packaged food classification. It employs a deep learning-based computer vision model trained from a representative dataset to achieve high classification accuracy. With the inclusion of a large nutritional database, NutriVision provides the user with rich nutrition information, which can be utilized for appropriate dietary choice and monitoring of individual nutrition. This paper presents an analysis of CNN architecture efficiency for food categorization, comparison of the accuracy of the system via performance metrics, and exploration of real-world deployment challenges implications. Experimental results validate the efficiency and stability of the model, placing NutriVision as a worthy AI-based system for automated food recognition and nutritional control.
Authors: Dhadake, Prof. S. B., Gandhi, Shreyas, Karmalkar, Chaitanya, Kharate, Akshay, Pande, Yash
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
SDG: Zero hunger
Open Access status: green
OpenAlex ID: W6930759824
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