Food Calorie Estimation Using Convolutional Neural Network

Abstract

The modern world healthy body depends on the number of calories consumed, hence monitoring calorie intake is necessary to maintain good health. At the point when your Body Mass Index is somewhere in between from 25 to 29. It implies that you are conveying overabundance weight. Assuming your BMI is more than 30, it implies you have obesity. To get in shape or keep up the solid weight individuals needs to monitor the calorie they take. The existing system calorie estimation is to be happened manually. The proposed model is to provide unique solution for measuring calorie by using deep learning algorithm. The food calorie calculation is very important in medical field. Because this food calorie is provide good health condition. This measurement is taken from food image in different objects that is fruits and vegetables. This measurement is taken with the help of neural network. The tensor flow is one of the best methods to classify the machine learning method. This method is implementing to calculate the food calorie with the help of Convolutional Neural Network. The input of this calculated model is taken an image of food. The food calorie value is calculated the proposed CNN model with the help of food object detection. The primary parameter of the result is taken by volume error estimation and secondary parameter is calorie error estimation. The volume error estimation is gradually reduced by 20%. That indicates the proposed CNN model is providing higher accuracy level compare to existing model.