Award Data

The video surveillance industry is experiencing dramatic change with the move from analog to digital video. Command centers need to have coordinated viewing of multiple camera feeds at one time, and the ability to switch automatically between feeds and display relevant patterns. Conventional security control rooms include a bank of monitors connected through a switch to an array of security camera ...

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 ...

Deep Convolutional Neural Networks (DCNNs) have become ubiquitous in the analysis of large datasets with geometric symmetries. These datasets are common in medicine, science, intelligence, autonomous driving and industry. While analysis based on DCNNs have proven powerful, uncertainty estimation for such analyses has required sophisticated empirical studies. This has negatively impacted the effect ...

For effective protection against radiated threats, it is important to understand not only the physics of the threats, but also to quantify the effects they have on mission-critical electrical systems. Radiated vulnerability and susceptibility testing requires delivery of high peak power and peak electric fields to distant targets. The most practical solution to simulate such environments on large ...

For effective protection against radiated threats, produced by high altitude electromagnetic pulse (HEMP) caused by nuclear detonations and high-power microwave (HPM) Directed Energy (DE) weapons it is important to understand not only the physics of the threats, but also to quantify the effects on mission-critical electrical systems. EMP/HMP simulators enable threat level testing of MCS and provid ...

Toyon Research Corporation (Toyon) and the University of California, Santa Barbara (UCSB) propose research, development, and demonstration of algorithms and an efficient software prototype for 3D model reconstruction using single images collected via remote sensing. In particular, the effort is focused on processing of high-resolution commercial satellite images for 3D reconstruction of buildings. ...

This program will demonstrate how additive manufacturing technologies can be used with reactive and high energy materials to create rapid and flexible fabrication of payload and munitions. Our primary approach to this problem will be to use powder bed binder printing techniques to print reactive structures. The anticipated feedstock will consist of composite particles containing all reactant spe ...

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 ...

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 which will enable wide dynamic range temperature me ...

On this effort Toyon Research Corp. and The Pennsylvania State University are developing deep learning-based algorithms for object recognition and new class discovery in look-down infrared (IR) imagery. Our approach involves the development of a hybrid classifier that exploits both transfer learning and semi-supervised paradigms in order to maintain good generalization accuracy, especially when li ...