Computer model developed by data sciences capstone students advances state-of-the-art image classification.
July 30, 2020

UNIVERSITY PARK, Pa. — This spring, students in the data sciences capstone course at the College of Information Sciences and Technology (IST) worked with a team of MIT Lincoln Laboratory Beaver Works researchers to make real-world contributions toward improving image classifiers for disaster response. 

Through the semester-long project, the student team analyzed the group’s Low Altitude Disaster Imagery (LADI) dataset — a collection of aerial images taken above disaster scenes — and tagged images based on the photograph’s content. This dataset was developed by the New Jersey Office of Homeland Security and Preparedness and MIT Lincoln Laboratory, with support from the National Institute of Standards and Technology and Amazon Web Services (AWS). The project is based upon work supported by the United States Air Force.

“We met with the MIT Lincoln Lab team last June and recognized shared goals around improving annotation models for satellite and LADI objects as we’ve been developing similar computer vision (CV) solutions here at AWS,” said Mike Shim, software development manager at AWS New Initiative. “We connected the team with MLRA and the Open Data Program and funded MTurk credits for the development of MIT Lincoln Laboratory’s ground truth data set.”