The food industry uses artificial intelligence (AI) to enhance food quality and security while
proposing significant capital savings and resource optimization. Additionally, understanding …

Advancements in computer vision have resulted in significant breakthroughs across various
applications, and one notable area of progress is in the recognition of food ingredient types …

Ingredient recognition has received significant attention due to its numerous industrial
applications, such as intelligent retail terminals and intelligent cooking devices. However …

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

This paper introduces a new approach for food image segmentation utilizing the Segment
Anything Model (SAM) with the additional refinement achieved through fine-tuning with Low …

Diabetes has emerged as a worldwide health crisis, affecting approximately 537 million
adults. Maintaining blood glucose requires careful observation of diet, physical activity, and …

Food cooking process are complex dynamical systems to model. In the state of the art we
find that a good solution consists of physics-based finite element models (FEM). FEM …

Food image classification, an interesting subdomain of Computer Vision (CV) technology,
focuses on the automatic classification of food items represented through images. This …

Rice stands as a favored and extensively consumed cereal grain in Asian countries, while
also enjoying global accessibility. Within the rice market, the overarching determinant of …

Food classification is crucial for the food industry and has a significant impact on public
health and nutrition. Deep learning techniques such as YOLOv5 and YOLOv7 have recently …