Award Data

A chemical threat agent mode of action is often initiated through a selective interaction with a biological molecule or structure. The binding event mimics normal cellular processes, but then overruns natural control mechanisms leading to toxic and lethal effects. The native binding specificity is used to design sensor recognition elements that outperform conventional antibody-based biosensors. Ou ...

This Phase-II SBIR proposal directly addresses the need to improve the size, weight and power, SWaP, of optical cryocoolers. In particular, the proposers will work toward increasing the efficiency of optical cryocoolers by incorporating cooling materials that require less input laser power to achieve a given heat lift. The new cooling materials will be high-purity crystals doped with active rare-e ...

Electro-optical infrared and long wavelength infrared detectors and sensors are increasingly important for the Chemical/Biological Defense community. Solid-state optical cooler materials are in demand for replacing mechanical closed cycle coolers used in current LWIR standoff sensors to achieve cryogenic temperatures. Recent advances in optical cooling of rare-earth doped materials are pointing to ...

Toyon Research Corporation proposes to develop algorithms that improve the precision and recall of neural networks for low-shot object classification and detection. Our approach is based upon developing a descriptive multi-domain feature representation of the low-shot target as well as the surrounding context. A multi-branch neural network merges the various domains of information to perform accur ...

Topographic features found in ground-based natural images contain information that is useful for a variety of applications including geolocation estimation and navigation. Traditionally, these features have been manually labeled by analysts which is costly and time consuming, especially considering the volume of readily available data. During Phase I, we have demonstrated a novel TOFENet framework ...

Toyon proposes to research and develop algorithms for generalized salient change detection, and to incorporate these algorithms into software tools implemented on the cloud. Our approach leverages the two most promising methods from Phase I, both based on supervised learning. The first method is the entropy-based feature vector and corresponding neural network, which we will apply at a coarse sear ...

With the explosive growth of Internet of Things (IoT) and mobile communication technologies, media streaming service and applications based on video content have gained remarkable popularity and interest from users. When someone is using their device to record a video, then share that video with friends through a certain website (e.g. Netflix, YouTube), the process may sound simple from the user s ...

Burkholderia pseudomallei and Burkholderia mallei are highly pathogenic Gram - negative bacteria and the causative agents of melioidosis and glanders, respectively. These infections, which occur in humans and other animals, are endemic is wide regions of the developing world. This Phase II SBIR project will build on the success of our Phase I work, which established methods for generating monoclon ...

Implement methods to improve our Phase I architecture for complex SAR imagery collected from different systems and with different collection parameters. Implement techniques to boost performance across all ground features of interest. Reduce the amount of human intervention needed for training our SAR image segmentation architecture.  SAR segmentation can be applied to a number of areas: Intellig ...

To address the CBD’s need for real-time analytical technology for multicomponent vapor identification and quantification, Physical Optics Corporation (POC) proposes to continue the development of a new Photoacoustic Gasses Optical Detector and Analyzer (PAGODA) autonomous, network-enabled photoacoustic spectrometer (PAS) for the correlation, analysis, and identification of measured spectra. In t ...