Comment Toxicity Detection Using Deep Learning

Abstract

This project explores a deep learning-based approach to accurately estimate the calorie content in food and beverages using image recognition techniques. As more individuals become health- conscious and seek to monitor their daily caloric intake, there is an increasing demand for a reliable and automated system that can estimate calories from food images combined with nutritional data. The model is trained on diverse food categories to improve prediction accuracy, even under varying environmental and lighting conditions.
The goal of this application is to provide users with a convenient platform where they can simply take a photo of their meal and receive nutritional information, promoting healthier eating habits and supporting diet management.
In addition to the core deep learning model, the project includes a user-friendly interface designed for real-time calorie estimation, accessible via web or mobile devices. The interface is intentionally designed to be intuitive, requiring minimal user input, thereby making it easier for users to adopt healthier lifestyles.
Ultimately, this solution not only fosters healthy eating and diet tracking but also represents a significant step forward in AI-driven healthcare applications, merging image recognition technology with nutritional monitoring to empower users in managing their health