Analysis of Nutrition Using Image Classification and CNN

Abstract

Abstract: Food is a necessity for human survival, as evidenced by several medical conferences. People today are more concerned with their diet and food choices to prevent developing or existing ailments. In order to prevent obesity and chronic diseases that are linked to dietary consumption, nutrition management is a crucial component of day-to-day life. Due to people's dependence on smart technologies, using nutrition analysis tools helps individuals understand their everyday eating habits, study nutrition trends, and maintain a balanced diet. In this case, we create a deep prototype food recognition system to examine and research food components from photos of regular meals This research aims to analyze the nutrient content of meals using picture classification. Unlike traditional artificial neural networks, convolutional neural networks can estimate the scoring function directly from image pixels. There are a number of these layers, and the outputs are concatenated at various points to get the final tensor of outputs. We used convolutional neural networks (CNN) to automatically determine the nutritional value of images.