This week, I worked with my teammates on the Design Review presentation slides and document. During our lab session, we discussed the details of the user flow diagram and wireframe of the phone application. We also decided what will be our design and implementation plans for the learning system of the application, which enables the application to recommend what item to bring at a certain time based on the user’s past behavior.
For the item recognition part, I watched Summary of Machine Learning Recipes with Josh Gordon from Google Developers. This playlist allowed me to learn about building a suitable model and training this model for the image classifier, which is what I want to accomplish for the item recognition part of the application. Training the model will be accomplished by scraping the images of the items from Google or other search engines and learning the features of the images. I also watched the Udemy course named Image Recognition with Neural Networks from Scratch. This lecture showed the mathematical concepts behind neural networks and how a neural network is accomplished to complete the task of recognizing an item. These two lectures and the blogpost guided me a lot to finalize my design of the item recognition pipeline, which uses Convolutional Neural Network (CNN) model.
My progress is currently on schedule.
Next week, I plan on starting the implementation of the item recognition classifier. From the list of items set up from last week, I will begin collecting the data (a collection of images) for the items that students carry in their backpacks. Since our team has our GitHub repository set up, I hope to share my progress with my teammates!