The project “Deep Learning for Classroom Augmented Reality Android App” is a second project having the same goal as the previous one – creating an android app that will allow, using an image of a drawing of a physical system, to create a running simulation of the said physical system. The goal of this project, similar to that of the previous project didn’t succeed, and as part of the overall solution, is to classify and localize different objects in the drawing of the physical system. Our project tries (and usually succeeds) to do so using deep learning algorithms, as opposed to the previous project that tried and hasn’t managed to do so using classic image processing algorithms. In the first stage of the project, we created a Convolutional Neural Network (CNN) that is able to classify specific objects that we defined as plausible to appear in physical system. After achieving high classification accuracy in the first stage, we moved to the second stage - creating a tagged dataset of drawings of different physical systems, and training a CNN to both classify and identify the locations of objects within the image of the overall physical system.