Summary of Nutrifyai: An Ai-powered System For Real-time Food Detection, Nutritional Analysis, and Personalized Meal Recommendations, by Michelle Han et al.
NutrifyAI: An AI-Powered System for Real-Time Food Detection, Nutritional Analysis, and Personalized Meal Recommendations
by Michelle Han, Junyao Chen, Zhengyuan Zhou
First submitted to arxiv on: 20 Aug 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Artificial Intelligence (cs.AI)
GrooveSquid.com Paper Summaries
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The proposed system combines computer vision techniques with nutritional analysis to create a comprehensive mobile and web application that can accurately identify food items, analyze their nutritional content, and offer personalized meal recommendations. The system consists of three key components: food detection using the YOLOv8 model, nutrient analysis via the Edamam Nutrition Analysis API, and personalized meal recommendations using the Edamam Meal Planning and Recipe Search APIs. Preliminary results demonstrate the system’s effectiveness in providing immediate and accurate dietary insights, with a food recognition accuracy of nearly 80%. This system has the potential to revolutionize the way users interact with nutrition applications, making informed dietary decisions more accessible. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary A new mobile and web application is being developed that can help people make better choices about what they eat. Right now, most health apps require you to manually enter information about your food, which can be time-consuming and boring. This app will use a special computer algorithm called YOLOv8 to recognize the food you’re eating, then tell you how many calories it has and suggest healthy meal options based on that information. The developers tested this app and found that it correctly identified foods almost 80% of the time. This could be a very useful tool for people who want to eat healthier but don’t have the time or knowledge to do all the work themselves. |
