ArticleFrontiers in nutrition2022
Eliminate the hardware: Mobile terminals-oriented food recognition and weight estimation system.
Article in Frontiers in nutrition, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 3 of them syntheses that pooled it.
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Who cites it
8 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Empowering Diabetics: Advancements in Smartphone-Based Food Classification, Volume Measurement, and Nutritional Estimation.Sensors (Basel, Switzerland) · 2024Pooled it
- Technology to Automatically Record Eating Behavior in Real Life: A Systematic Review.Sensors (Basel, Switzerland) · 2023Pooled it
- AI-based digital image dietary assessment methods compared to humans and ground truth: a systematic review.Annals of medicine · 2023Pooled it
- YOLO-MCD: An Efficient Detection Method for Multi-Dish Recognition.Journal of food science · 2026Article
- RulerNet: Learning perspective-invariant ruler representations for robust image scale estimation.Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society · 2026Article
- [Application of Digital Nutrition Technologies in Adult Weight Management].Sichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition · 2025Article
- Enhancing food recognition accuracy using hybrid transformer models and image preprocessing techniques.Scientific reports · 2025Article
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Food recognition and weight estimation based on image methods have always been hotspots in the field of computer vision and medical nutrition, and have good application prospects in digital nutrition therapy and health detection. With the development of deep learning technology, image-based recognition technology has also rapidly extended to various fields, such as agricultural pests, disease identification, tumor marker recognition, wound severity judgment, road wear recognition, and food safety detection. This article proposes a non-wearable food recognition and weight estimation system (nWFWS) to identify the food type and food weight in the target recognition area
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Registered trials
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