NOVEL DEVICE TO DETECT FOOD CALORIES USING MACHINE LEARNING

Authors

  • Chaitanya krishna Suryadevara Department of Information Systems Senior Researcher and Software Engineer

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. The "DeepCalorie" device, with its user-friendly interface, 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

2023-09-30

Issue

Vol. 10 No. 9 (2023): IJIERT

Section

Articles

License

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How to Cite

Chaitanya krishna Suryadevara. (2023). NOVEL DEVICE TO DETECT FOOD CALORIES USING MACHINE LEARNING. International Journal of Innovations in Engineering Research and Technology, 10(9), 52-61. https://repo.ijiert.org/index.php/ijiert/article/view/3674