Estimating Indian Food Calorie With Convolution Neural Networks

Accurate estimation of food calories plays a crucial role in promoting healthy eating habits and managing diet-related health conditions.Indian cuisine presents unique challenges in this domain due to its rich diversity, complex food compositions, and varied preparation methods.In this study, we propose a deep learningbased approach for automatic calorie estimation of Indian food using Convolutional Neural Networks (CNNs).Our system leverages a large dataset of labeled Indian food images, annotated with corresponding calorie information.We employ CNN architectures to classify food items and estimate portion sizes, followed by a mapping to nutritional databases to predict caloric values.To address intra-class variations and occlusions common in Indian dishes, we incorporate techniques such as image augmentation, transfer learning, and ensemble modeling.Experimental results demonstrate promising accuracy in calorie estimation across a wide range of Indian foods.This work has the potential to aid in the development of mobile health applications for personalized dietary monitoring and nutrition tracking in diverse cultural settings.