Background: Maintaining a healthy diet is vital to avoid health-related issues, eg,
undernutrition, obesity and many non-communicable diseases. An indispensable part of the …

Dietary assessment can be crucial for the overall well-being of humans and, at least in some
instances, for the prevention and management of chronic, life-threatening diseases. Recall …

Food image classification is challenging for real-world applications since existing methods
require static datasets for training and are not capable of learning from sequentially …

Deep learning based food recognition has achieved remarkable progress in predicting food
types given an eating occasion image. However, there are two major obstacles that hinder …

Numerous deep learning methods have been developed to tackle the challenges of
recognizing food images, including convolutional neural networks, deep feature extraction …

In the present society, many people are suffering from diabetes. To maintain a healthier diet,
people must track the number of food calories they consume daily, along with their total …

Food classification serves as the basic step of image-based dietary assessment to predict
the types of foods in each input image. However, foods in real-world scenarios are typically …

Dietary assessment is a key contributor to monitoring health status. Existing self-report
methods are tedious and time-consuming with substantial biases and errors. Image-based …

Deep learning based food image classification has enabled more accurate nutrition content
analysis for image-based dietary assessment by predicting the types of food in eating …

Image-based dietary assessment serves as an efficient and accurate solution for recording
and analyzing nutrition intake using eating occasion images as input. Deep learning-based …