The team includes experts from Mitre, Johns Hopkins University Applied Physics Laboratory, U.S. Geological Survey, Savannah River National Laboratory and NASA’s Goddard Space Flight Center.
The SMART program seeks to detect, characterize and monitor heavy construction, crop growth and other manmade and natural changes by automating space-based imagery analysis using machine learning and global-scale image processing.
“Current manual exploitation methods do not scale well with the data volumes we’re receiving, and there’s the problem of simultaneously analyzing data from past, current and future space-based systems,” said IARPA Program Manager Jack Cooper. "SMART innovations in data fusion and machine learning techniques will enable automated broad area search at unprecedented temporal resolution and area coverage."
NexTech Solutions, a mission-driven provider of edge-focused software and services, has acquired Vidterra, a developer of edge-deployed video distribution software, to…