Nutrition
29 papers with code • 1 benchmarks • 1 datasets
Most implemented papers
Scaling Language Models: Methods, Analysis & Insights from Training Gopher
Language modelling provides a step towards intelligent communication systems by harnessing large repositories of written human knowledge to better predict and understand the world.
Learning Cross-Modal Embeddings with Adversarial Networks for Cooking Recipes and Food Images
Food computing is playing an increasingly important role in human daily life, and has found tremendous applications in guiding human behavior towards smart food consumption and healthy lifestyle.
FoodTracker: A Real-time Food Detection Mobile Application by Deep Convolutional Neural Networks
We present a mobile application made to recognize food items of multi-object meal from a single image in real-time, and then return the nutrition facts with components and approximate amounts.
An Open-Source Dataset on Dietary Behaviors and DASH Eating Plan Optimization Constraints
We hope that this data and its supplementary, open-accessed materials can accelerate and simplify interpretations and research on linear optimization and constrained inference models.
Nutribullets Hybrid: Multi-document Health Summarization
We present a method for generating comparative summaries that highlights similarities and contradictions in input documents.
MUSEFood: Multi-sensor-based Food Volume Estimation on Smartphones
Furthermore, MUSEFood uses the microphone and the speaker to accurately measure the vertical distance from the camera to the food in a noisy environment, thus scaling the size of food in the image to its actual size.
Market2Dish: Health-aware Food Recommendation
With the rising incidence of some diseases, such as obesity and diabetes, a healthy diet is arousing increasing attention.
Personalized Food Recommendation as Constrained Question Answering over a Large-scale Food Knowledge Graph
Food recommendation has become an important means to help guide users to adopt healthy dietary habits.
Nutrition5k: Towards Automatic Nutritional Understanding of Generic Food
Understanding the nutritional content of food from visual data is a challenging computer vision problem, with the potential to have a positive and widespread impact on public health.
Nutri-bullets: Summarizing Health Studies by Composing Segments
We introduce \emph{Nutri-bullets}, a multi-document summarization task for health and nutrition.