Machine Learning for Network-Denied Environments

Machine Learning for Network-Denied Environments (MINDE) is an A.I. tutoring system that takes images and classifies them to the correct labels. The images can be snapped from a phone or uploaded from the photo gallery on to the cloud server to be classified. This tool can be used offline and updates the server automatically when a network is available. This is done by constantly adapting the model through the code with the use of model training. MINDE has a friendly user interface that can be used through a mobile client. There will be a label and confidence to determine how certain the A.I. perceives the image. The tool's main purpose is to set up an available A.I. tutoring system that is made to work when offline and automatically updates when back online. This is achieved by having the tool accept images and passes them through a set of labels that are already in the server and then gives out the correct response. If an image is not classified by the labels, then the user is able to add a new label for future classification. 

Student Team
  • Sanjog Baniya
  • Jonathon M Dooley
  • Enrico Efendi
  • Wilson Gan
  • Xavier Lara
  • Kevin Maravillas
  • Howard Nguyen
  • Nisapat Poolkwan
  • Johnson Tan
  • Justin To
  • Alvin Yu
Project Sponsor
Project Liaisons
Faculty Advisors
  • Chengyu Sun