The Impact of Computer Vision on Assisting Visually Impaired People

This research aims to develop computer vision algorithms that can provide accurate positioning data from video input, with the goal of creating a program to assist visually impaired individuals in navigating their environment.

In today’s world, artificial intelligence has been a significant new innovation. One of the prime aspects of artificial intelligence is its ability to perform computer vision, which is using machine learning to allow a computer to detect things, via camera or sensors. Computer vision has seen significant development in the past years which can be used to help people who struggle with vision. This research focuses on developing computer vision algorithms to output positioning data for people to see. It includes several steps in the coding process, such as creating an object detection model, a positioning algorithm, and finally manipulating videos to project an output. The goal of this research will be to create a working program that can take a sample video and output correct positioning instructions for a user. This work will hopefully transform the way the visually impaired can navigate the world.

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Predictive Modeling of Diabetes Using Python Neural Networks

This research develops a neural network model using machine learning to predict diabetes occurrence, achieving strong accuracy and performance metrics, and highlights the need for ongoing model improvements to enhance early detection and healthcare for at-risk individuals.

Advik V.

Mentored by Ronil Synghal

Using Machine Learning Models to Predict Heart Disease and Attack with Non-Clinical and Non-Wearable Variables

This study uses data from the CDC’s Behavioral Risk Factor Surveillance System (BRFSS) to train machine learning models that predict heart disease risk based on non-clinical factors. The research demonstrates the potential for cost-effective, data-driven screening tools for early heart disease detection, though further improvements are needed for real-world application.

Samuel P.

Mentored by Rami Abi-Akl

Predicting Skin Cancer using Machine Learning

Skin cancer affects an increasing number of people which is the main motivation for my research. The goal is to develop a model that is accurate enough for real world application and that could be distributed to more rural areas which have decreased access to medical technology.

Keithan P.

Mentored by Eric Bradford

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The Impact of Computer Vision on Assisting Visually Impaired People

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Research Paper