Ismael Resendiz

Facemask Detection

During COVID-19 outbreak the World Health Organization issue recommendations and new practices, all in-door public places like grocery stores, shopping malls, movie theaters, etc. requiring their customers to wear facial mask to enter. However, enforcing to wear mask in large amounts of customers may be a complicated task for a human to do. Considering that most public places count with surveillant systems with cameras, these systems can be repurposed to automate face mask detection on the customer.

The objective of this project is to apply deep learning algorithms to perform face mask detection on real-time videos and photos. Specifically, this project experiments with few Convolutional Neural Networks (CNN) that perform object classification.

Heart Disease Prediction

Based on the Center for Disease Control and Prevention, heart disease is the leading cause of deth for men and women of most racial and etnic groups in the U.S. One person dies every 36 seconds in the U.S. from cadiovascular disease. This makes heat disease a major concern to be deal with. And it might be difficult to identify heart diseas because of seveal risk factors such as age, high blood pressure, high colesterol, and many other.

The purpose of this project is to explore existing Machine Learning algorithms which can solve the heart disease prediction problem and experiment with different heart disease datasets.

WebRTC Video conference

Peer-to-peer video conference is an module that can be adapted to any web or mobile application. It allows users to create video chat rooms and share the link with others to join. It is a prototype that may require additional work to scalate it to support large number or participants at the same time.