A NOVEL MACHINE LEARNING APPROACH TO CALORIE ESTIMATION FOR DIABETES AND OBESITY MANAGEMENT

Authors

  • Venkata Ravi Kiran Kolla Sr. Research Scientist Department of ML & AI Sr. Engineer at DTE Energy South Lyon, MI

DOI:

https://doi.org/10.26662/ijiert.v11i12.pp8-16

Keywords:

Machine learning, Deep Learning, nutrition, calorie, technique.

Abstract

In an era where dietary choices significantly impact health and wellness, the accurate assessment of calorie intake is of paramount importance. "DeepCalorie" presents an innovative food calorie detection device that leverages state-of-the-art machine learning techniques. This device aims to empower individuals with the ability to effortlessly estimate the calorie content of their meals by simply capturing images. The system utilizes a diverse dataset of food images, deep neural networks for feature extraction, and sophisticated algorithms to estimate calorie counts. Furthermore, it offers the option to assess portion sizes, providing a more comprehensive dietary analysis. With its user-friendly interface, the "DeepCalorie" device represents a promising step towards promoting healthier eating habits and fostering nutrition awareness. This paper details the development process, challenges encountered, and the potential impact of this technology on improving dietary choices and overall well-being.

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Published

2024-12-19

Issue

Vol. 11 No. 12 (2024): IJIERT

Section

Engineering and Technology

License

Copyright (c) 2024 International Journal of Innovations in Engineering Research and Technology

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