DEEP LEARNING BASED FOOD CALORIE DETECTION SYSTEM

DEEP LEARNING BASED FOOD CALORIE DETECTION SYSTEM

Manjusha K Kavatekar 1 , Dr. Geetha M 2

[1] Student, Department of MCA, BIET, Davangere.

[2]Associate Professor, Department of MCA, BIET, Davangere.

ABSTRACT
The prevalence of diet-related health issues underscores the significance of accurate nutritional assessment for maintaining healthy lifestyles. With the ubiquity of smartphones and the increasing interest in health monitoring, there is a growing demand for convenient and reliable methods to track dietary intake. In this paper, we propose a Deep Learning-Based Food Calorie Detection System (DL-FCDS) that leverages computer vision techniques to automatically estimate the caloric content of foods from images captured using smartphones or other portable devices. Our system combines state-of-the-art deep learning models with image processing algorithms to detect and classify various food items within images, subsequently estimating their caloric content based on portion size and nutritional composition

Keywords: Deep Learning, Food Calorie Detection, Computer Vision, Nutritional Assessment, Dietary Monitoring, Convolutional Neural Networks.