Award Data

Through the proposed SBIR program, NanoSonic shall design, fabricate, test, and validate an environmentally robust, fluorine-free elastomeric composite barrier material for class 1 NFPA 1994 certified chemical, biological, radioactive, and nuclear (CBRN) protective ensembles. The material shall be chemically resistant against the liquid and vapor challenge chemicals listed in NFPA 1994 and shall m ...

TP Engineering personnel have extensive experience with electro-optic systems and high Pulse Repetition Frequency (PRF) Laser systems. We have detailed knowledge of Pockels cell systems enabling active gated imaging through foliage at PRF 100 kHz PRF. Such systems can dramatically improve and protect Geiger-mode LIDAR by both controlling the transmitter output and gating out unwanted return lig ...

CoVar’s DOCTRINAIRE is a new approach to computer aided object annotation that is modeled after the way expert end-users leverage generic, robust background information (e.g., what wheels look like) and known doctrine (the size and shape of components on a pickup truck) to perform reliable, explainable object detection and annotation. Our approach solves the robustness problem by training a reli ...

The ubiquity of image sensors for data collection creates a glut of data, which leads to bottlenecks in the processing capabilities of modern systems. In order to process this data, meticulously labeled datasets are required and that must be reviewed by humans in order to guarantee state-of-the-art performance. In this effort we endeavor to create a system that can automatically exploit salient in ...

We propose an innovative all ALD approach to achieve super enhancement, ultra-sensitive SERS active substrates which also offers not only high reproducibility, high performance consistency and reliability, but also low cost and scalability for high volume manufacturing. Our key innovations include: 1) Porous polymer filter membranes with uniformly distributed and uniformly sized fine surface featu ...

In the pattern of life problem space, data is often represented via mathematical graphs, in which a variety of algorithms may be employed to conduct semi-autonomous analysis. While successful empirical application of graph-domain algorithms on ABI problems has been achieved, most of these algorithms require a tuning parameter, which is often set heuristically in real-world scenarios. Arete has dev ...

The primary goal of this proposed project is to develop a general-purpose technique for the problem of algorithm parameter selection (APS) that achieves the best performance of the algorithm and demonstrates its effectiveness within graph analysis, for the problem of community detection, or clustering.  Cell Matrix Corporation (CMC) will develop a means to greatly simplify the tweaking typically ...

Concealed chemical threats represent a significant hazard to field operators. Even brief exposure to chemicals can cause lasting physical, physiological, and mental damage. Field operators require tools and techniques to more quickly, safely, and reliably locate and identify chemical threats. Chemical detectors typically excel at either threat classification or threat localization, but seldom both ...

To address the Chemical and Biological Defense (CBD) agency’s need for a new deep learning (DL)-based threat detection solution that fuses imaging sensors and chemical/biological sensors to detect and locate concealed chemical threats, Intellisense Systems, Inc. (Intellisense) proposes development of a new Chemical-Imaging Registration and Multimodal Analysis (CIGMA) solution. CIGMA will compris ...

This SBIR Phase I project proposes development of deep learning based chemical threat detection and localization framework that exploits multiple sensor data streams including imaging and chemical sensors. The proposed technologies combine deep hypernetworks and reinforcement learning techniques to fuse sensor data streams in an online fashion. Novateur team will perform training of deep networks ...