Award Data

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 ...

While aluminum casing materials provide some enhanced performance and thermal loading to explosive ordinance, their overall effectiveness is highly limited by incomplete combustion and long residence times. In order to reduce these problems, the casing material must be designed to facilitate rapid fragmentation through either specialized casing geometries or greatly refined initial particle sizes. ...

Establish a radiation-aware analysis capability in a commercial EDA design flow that will enable first-pass success in radiation-hardened by design (RHBD) for DoD ASICs in much the same way that existing EDA design suites ensure first pass functionality and performance success of complex ASICs destined for commercial applications. Layout-aware, calibrated single-event radiation models that captur ...

There is significant interest in multi-functional materials enabling gamma-ray spectroscopy, neutron/gamma pulse shape discrimination (PSD), ultra-fast response, and time-of-flight (TOF) neutron detection. These materials would be used in a variety of mission scenarios for the localization and monitoring of special nuclear materials. Commercial inorganic scintillators offer some of these character ...

Military operators must identify and catalogue the equipment they find when inspecting laboratory facilities. This information is used to determine the lab’s capabilities, including the lab’s potential for building weapons of mass destruction. Currently, operators use computer vision algorithms to help them classify equipment in pictures of laboratory environments. Unfortunately, current image ...