JomImageProcessing: Machine Learning Weight Control with SnapFudo
Keywords:
food, calorie, healthy, weight loss, obesity, overweight, image recognition, food recognitionAbstract
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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Copyright (c) 2021 Journal of Telecommunication, Electronic and Computer Engineering (JTEC)
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)