Food Recognition

Food recognition, using computer vision and machine learning, aims to automatically identify and categorize food items from images, facilitating applications in dietary assessment, health management, and food production. Current research emphasizes improving the accuracy and efficiency of food recognition models, particularly addressing challenges like fine-grained classification (distinguishing visually similar foods), handling diverse real-world scenarios (beyond controlled settings), and adapting to continuously evolving food data through continual learning techniques. These advancements are significant for improving personalized dietary interventions, reducing food waste, and enhancing the efficiency of various food-related industries.