The U.S. Department of Homeland Security recently awarded funding to two small businesses to develop non-contact, inexpensive machine learning training and classification technologies.
Physical Sciences Inc., Andover, Mass., and Alakai Defense Systems Inc., Largo, Fla., each received approximately $1 million in Phase II funding from the Small Business Innovation Research Program to develop technologies that can rapidly and accurately identify unknown spectrometer signals as safe or threatening.
Physical Sciences in Phase II will continue to develop its deep-learning algorithm for detection and classification of trace explosives, opioids, and narcotics on surfaces for optical spectroscopic systems. Alakai will continue development of the Agnostic Machine Learning Platform for Spectroscopy that rapidly and accurately detects trace quantities of hazardous and related chemicals from a variety of spectroscopic instruments.
"The SBIR Program provides the opportunity for S&T to partner with innovative small businesses and develop machine learning tools critical to addressing threat detection needs," says DHS Senior Official Kathryn Coulter Mitchell.
From U.S. Department of Homeland Security
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