JomImageProcessing: Machine Learning Weight Control with SnapFudo

Authors

  • P.S. JosephNg UCSI University, Malaysia
  • V. Vivilyana Malaysia

Keywords:

food, calorie, healthy, weight loss, obesity, overweight, image recognition, food recognition

Abstract

Tracking the calorie of food consumed is becoming harder when eating outside. With many fast food choices available almost everywhere, the consumption of fast food is high among Malaysian. While numerous calorie-tracking apps are available in the market, these apps require manual inputs that are frustrating yet demotivating. With the application of
machine learning, this study will involve image recognition of food to ease the food input for the user. From the survey data collected, most respondents are aware of Body Mass Index (BMI) but find it difficult to track their calorie intake, especially when eating out. Respondents also have difficulties identifying each ingredient and how much the quantity in their meals. As a result, the implemented apps can guide the user on losing weight healthily and motivating them to achieve their weight goals.

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Published

2021-06-28

How to Cite

JosephNg, P., & V. Vivilyana. (2021). JomImageProcessing: Machine Learning Weight Control with SnapFudo. Journal of Telecommunication, Electronic and Computer Engineering (JTEC), 13(2), 35–43. Retrieved from https://jtec.utem.edu.my/jtec/article/view/5890

Issue

Vol. 13 No. 2 (2021): April - June 2021

Section

Articles

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