Food Recognition
11 papers with code • 0 benchmarks • 8 datasets
Benchmarks
These leaderboards are used to track progress in Food Recognition
Datasets
Recipe1M+
FoodX-251
ISIA Food-500
ChineseFoodNet
KenyanFood13
CNFOOD-241-Chen
Indian Food Image Dataset
Latest papers with no code
A Real-time Junk Food Recognition System based on Machine Learning
The goal was achieved using Convolution Neural Network (CNN) technology, which is well-known for image processing.
A review on vision-based analysis for automatic dietary assessment
We also provide the latest ideas for future development of VBDA, e. g., fine-grained food analysis and accurate volume estimation.
VinaFood21: A Novel Dataset for Evaluating Vietnamese Food Recognition
We use 10, 044 images for model training and 6, 682 test images to classify each food in the VinaFood21 dataset and achieved an average accuracy of 74. 81% when fine-tuning CNN EfficientNet-B0.
Egocentric Image Captioning for Privacy-Preserved Passive Dietary Intake Monitoring
In this paper, we propose a privacy-preserved secure solution (i. e., egocentric image captioning) for dietary assessment with passive monitoring, which unifies food recognition, volume estimation, and scene understanding.
The Food Recognition Benchmark: Using DeepLearning to Recognize Food on Images
The automatic recognition of food on images has numerous interesting applications, including nutritional tracking in medical cohorts.
A Comprehensive Survey of Image-Based Food Recognition and Volume Estimation Methods for Dietary Assessment
First, we will present the rationale of visual-based methods for food recognition.
Large Scale Visual Food Recognition
Food2K can be further explored to benefit more food-relevant tasks including emerging and more complex ones (e. g., nutritional understanding of food), and the trained models on Food2K can be expected as backbones to improve the performance of more food-relevant tasks.
An End-to-End Food Image Analysis System
Our end-to-end framework is evaluated on a real life food image dataset collected from a nutrition feeding study.
The Diabetic Buddy: A Diet Regulator andTracking System for Diabetics
In this regard, there is a need to build automatic tools to monitor the blood glucose levels of diabetics and their daily food intake.
Visual Aware Hierarchy Based Food Recognition
Experimental results demonstrate that our system can significantly improve both classification and recognition performance on 4 publicly available datasets and the new VFN dataset.
