Intelligent Food Recognition and Customized N...

Intelligent Food Recognition and Customized Nutrition Recommendation Framework

Author Name : M S Prapulla Kumar, Suhas K Gowda, Vinay Nagasara R, Srujan SS, Vishwas U R

DOI: https://doi.org/10.56025/IJARESM.2025.130725896

ABSTRACT In today’s fast-paced world, maintaining a balanced diet is often neglected due to busy lifestyles and the lack of awareness about nutritional intake. To address this issue, this research proposes an Intelligent Food Recognition and Customized Nutrition Recommendation Framework that leverages artificial intelligence to automatically identify food items from images and provide personalized dietary suggestions. The system employs a deep learning-based ResNet101 architecture integrated with a dual-head structure—one head for food classification and another for calorie regression. The model is trained on a diverse dataset of food images and corresponding nutritional data to accurately predict both the food type and its estimated calorie content. Furthermore, a personalized recommendation module is developed to suggest additional food items based on the user’s total calorie intake and nutritional requirements. Experimental results demonstrate that the proposed system achieves high accuracy in both classification and calorie estimation tasks, outperforming traditional manual approaches. This framework has the potential to assist individuals in monitoring their daily food consumption and making healthier dietary choices with minimal effort.