Dietary studies showed that dietary problems such as obesity are associated with other
chronic diseases, including hypertension, irregular blood sugar levels, and increased risk of …

Recognizing the category and its ingredient composition from food images facilitates
automatic nutrition estimation, which is crucial to various health relevant applications, such …

Ingredient prediction has received more and more attention with the help of image
processing for its diverse real-world applications, such as nutrition intake management and …

Recently, visual food analysis has received more and more attention in the computer vision
community due to its wide application scenarios, eg, diet nutrition management, smart …

It is important for food recognition to separate each ingredient within a food image at the
pixel level. Most existing research has trained a segmentation network on datasets with pixel …

Food recognition applications in human health have recently garnered significant attention
in the field of computer vision. With the advancement of mobile devices, robust food …

Accurate recognition of nutritional components in food is crucial for dietary management and
health monitoring. Current methods often rely on traditional chemical analysis techniques …

Deep convolutional neural networks (CNNs) have facilitated remarkable success in
recognizing various food items and agricultural stress. A decent performance boost has …

Generating food images from recipe and ingredient information can be applied to many
tasks such as food recommendation, recipe development, and health management. For the …

Effective software defect prediction (SDP) is important for software quality assurance.
Numerous advanced SDP methods have been proposed recently. However, how to …