Augmented Reality Sandbox
William Fleming, Harry Atwal, Yunkai Xaio, Renee Faust, Kevin Gay, Aljohnel Labsan, – CS and MS CSIS Students, Dr. Karl Ricanek – CS Faculty
PCB Circuit Board Vision System
Kevin Gay – CS Student, Jessica Baron – Clemson U., Dr. Karl Ricanek – CS Faculty
Tattoo & Piercing Dataset
Renee Faust, Kevin Gay, Harry Atwai, Yunkai Xaio, William Fleming, Aljohnel Labsan – CS and MS CSIS Students, Dr. Karl Ricanek – CS Faculty
The “Moxie” is a project that several students, including Harry Atwal, Yunkai Xiao, Nick Houghton, Reni Faust, and Ashley Teague, built in a couple weeks. It is a drink mixer that is voice controlled and ran by an Amazon Echo. It takes drink orders and can tell you information about lab members, important figures, and other information.
Detecting Body Mass Index From Facial Features
We are currently developing an app that will be able to predict a subject’s BMI simply by looking at a picture of their face.
Detecting Biological Age From Facial Features
We are currently developing an app that can analyze a subject’s face and detect their age. This is the same app we are using to guess BMI. The goal of the app is to be able to detect various health factors and diseases by doing facial scans. In order to train the AI, we travel to various festivals and ask people to be subjects.
Deep Fake Detection
Invasive Plantlike Species Detection
Because AI models are data-driven, the predictions or estimations made by the model will conform to the characteristics of the training data. In our study of algorithmic bias, we examine the sources of bias in modern deep neural networks and develop techniques for mitigating such bias.
Deep Learning Augmentation Policies
Deep learning requires the use of large datasets in order to train an accurate model. Data augmentation policies manipulate training data to effectively increase the size of the dataset and generalize the model while improving accuracy. This project involves using an evolutionary process to learn data manipulation techniques that improves AI decisions.
Data Collection Events
The Face Aging Group finds festivals to gather facial and survey data. This data helps propel our research in biometrics.