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.

Explore More!

Structure-Based Analysis of Parkinson’s Disease Protein Mutations: Comparative Analysis of Computational and Experimental SNCA Structures

This study uses AI-based protein modeling tools such as AlphaFold and ColabFold to compare wild-type and mutant α-synuclein structures in Parkinson’s disease, evaluating their interactions with pharmacologically relevant ligands. By integrating structure prediction with molecular docking, the research highlights both the potential and limitations of computational methods for understanding mutation-specific effects and guiding drug discovery efforts.

Arya S.

Mentored by Khanh Nguyen

Developing an Accurate AI Algorithm for Histopathologic Cancer Detection

In this specific research project, we will be focusing on the lymph node scans of women with breast cancer, which is the most common cancer for women residing in the US, other than skin cancer. Research statistics show that about 1 in 8 women in the United States will develop invasive breast cancer throughout her life.

Leah N.

Mentored by Odysseas Drosis

Using Machine Learning to Detect Parkinson’s Disease Through Drawing Data

This research explores the use of machine learning models, particularly logistic regression, on patients' spiral and wave drawings as an accessible and cost-effective method to improve Parkinson's disease diagnosis, achieving an accuracy of 91%, precision of 92%, and recall of 89%.

Katie Y.

Mentored by Sriram Hathwar

About Inspirit AI

Home Team Impact

Programs

Live Online Learn More Apply Now

Join Our Mailing List

Stay up to date with all things Inspirit AI!

Terms and conditions | Refund policy | Privacy policy

The Impact of Computer Vision on Assisting Visually Impaired People

Explore More!

Research Paper