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SBC: SA PHOTONICS, LLC Topic: DTRA19B001
Improving the effectiveness of counter-WMD operations requires improved understanding of weapon-target interaction. Specifically, time-resolved measurements of temperature and composition are required to allow temporal evolution of a detonation fireball. To address this need, SA Photonics will develop MONITOR, a laser-based temperature diagnostic that will enable wide dynamic range temperature mea ...STTR Phase I 2020 Department of DefenseDefense Threat Reduction Agency
SBC: Intelligent Automation, Inc. Topic: DTRA19B002
Current state-of-the-art object detection algorithms are almost exclusively based on Deep Convolutional Neural Network (DCNN). These algorithms all require a large amount of labeled examples for each of the object categories they can recognize. These algorithms will fail for novel objects that only very few or even no prior examples are available. These algorithms are also far less accurate when c ...STTR Phase I 2020 Department of DefenseDefense Threat Reduction Agency
SBC: RADIATION DETECTION TECHNOLOGIES, INC. Topic: DTRA18B002
Phase II will utilize knowledge gained from phase I work to develop and execute a manufacturing process suitable for producing quantities of 3-D printed discrete circuits for radiation detection systems. The goal is to support mobile radiation detection system requirements for high voltage, analog amplification, and MCA functionality to produce differential pulse height spectra in time sequence. ...STTR Phase II 2020 Department of DefenseDefense Threat Reduction Agency
SBC: SIGNATURE RESEARCH, INC. Topic: NGA18A001
The multidisciplinary area of GEOINT is changing and becoming more complex. A major driver of innovation in GEOINT collection and processing is artificial intelligence (AI). AI is being leveraged to help accomplish spatial analysis, change detection, and image or video triage tasks where filtering objects of interest from large volumes of data is critical. NGA is confronting the changing GEOINT l ...STTR Phase II 2020 Department of DefenseNational Geospatial-Intelligence Agency
SBC: Euler Scientific Topic: NGA20A001
Deep Neural Networks have become ubiquitous in the modern analysis of voluminous datasets with geometric symmetries. In the field of Particle Physics, experiments such as DUNE require the detection of particle signatures interacting within the detector, with analyses of over a billion 3D event images per channel each year; with typical setups containing over 150,000 different channels. In an ...STTR Phase I 2020 Department of DefenseNational Geospatial-Intelligence Agency