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The Award database is continually updated throughout the year. As a result, data for FY20 is not expected to be complete until September, 2021.
SBC: Clostra, Inc. Topic: DTRA162001
"Deep Learning for standoff detection of Special Nuclear Material (DLeN) applies the same deep learning techniques that allow computers to beat human performance in image recognition and the game of Go to detecting Special Nuclear Material. Spectral analysis and signal processing can in some cases be augmented by the use of much larger neural nets that conduct much deeper analysis of features of t ...SBIR Phase I 2017 Department of DefenseDefense Threat Reduction Agency
SBC: Hyperion Technology Group, Inc. Topic: DTRA143004
Traditional weapon systems often fail to meet the requirements of close combat typical of the previously discussed engagement, where insurgents often blend in or store weapon amongst friendly or non-combatant forces, to shield them from precision strike munitions of a technologically superior force. This type of warfare has led to an increased focus on the use of less-lethal weapons, to reduce let ...SBIR Phase II 2017 Department of DefenseDefense Threat Reduction Agency
SBC: Hyperion Technology Group, Inc. Topic: DTRA143007
In an effort to development more robust optical system coatings DTRA, in collaboration with Sandia National Labs, is working to characterize the degradation of optical materials for space systems when exposed to high intensely EUV/ cold x-rays. The experiments utilizes the Double Eagle z-pinch facility which generates high current, high voltage arc pinch plasma to produce an intense EUV and cold x ...SBIR Phase II 2017 Department of DefenseDefense Threat Reduction Agency