Verus Research Employing Machine Learning with Radiation Detectors

Verus Research has won a Phase I small business innovative research (SBIR) contract to support the Defense Threat Reduction Agency (DTRA).  Leveraging multiple machine learning and algorithm development efforts at Verus Research, the program will employ efficient machine learning algorithms to facilitate information fusion of radiation detector data.

The objective of the project is to improve radiation detection capabilities by developing networked radiation detection algorithms based on the fusion of multiple and varied raw outputs from detectors deployed across a complex, one square kilometer scene.  In this phase, Verus Research will identify algorithms that can support the fusion of raw detector outputs into usable information and demonstrate the potential of these algorithms to improve the localization, identification, and characterization of radioactive sources.  When successful, this will allow the evaluation of multiple candidate algorithms for eventual down-selection to the most promising ones for further development in an eventual Phase II program.