Abstract:
This project uses the Convolutional Neural Network techni
and content based filtering for recommendation
CNN is that it
que for image processing
system. The main advantage of using
automatically detects the important features without any human
supervision. Moreover, content based filtering does not need any data about other
users, since the recommendations are specific to the particular user. This makes it
easier to scale to a large number of users. The goal of this project is to create image
recognition algorithms that
can
user
identify ingredients from images and then
recommend recipes based on those ingredients. The recipes are also recommended
depending on the user’s BMI (Body Mass Index), which results in healthy recipes for
that person. This report examines various techniques for identifying ingredients. The
pre-processing step, segmentation, and feature extraction are just a few of the various
image processing phases that will be examined and discussed. The output of the
algorithms will then be written in the Colab notebook for the backend. The currently
build system is a mobile application that performs recommendation based on image
recognition and BMI of the user. If the user chooses to process images, the system
begins by doing a pre-process on the image after which it recommends recipes based
on the images it has recognized. If user selects for BMI, then the system first asks the
to enter his/her height and weight. The system then continues by calculating
BMI, after which recipes are recommended based on BMI to determine which ones
will be healthier for the user. The user can also search for recipes by simply writing
the names of ingredients
