TY - JOUR AU - JosephNg, P.S. AU - V. Vivilyana, PY - 2021/06/28 Y2 - 2024/03/29 TI - JomImageProcessing: Machine Learning Weight Control with SnapFudo JF - Journal of Telecommunication, Electronic and Computer Engineering (JTEC) JA - JTEC VL - 13 IS - 2 SE - Articles DO - UR - https://jtec.utem.edu.my/jtec/article/view/5890 SP - 35-43 AB - <p><span class="fontstyle0">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<br />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.</span> </p> ER -