Award Data

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 ...

A program to develop a compact, MLA-based, LWIR, full-motion-video hyperspectral imager for chemical detection is proposed. The proposed Hyperspectral Chemical Imaging Sensor (HyCIS) builds upon Surface Optics’ real-time hyperspectral imaging activities, including our 3D full-motion-video spectral imaging (FMV-SI) technology and our MIDIS hyperspectral image processor. Simultaneously sampling 16 ...

SA Photonics is please to submit the proposal for the HawkEye compact LWIR hyperspectral imaging system. HawkEye leverages SA Photonics previous visible, SWIR, and LWIR programs to result in a compact, hand held, battery operated hyperspectral imager in a low cost design approach. Furthermore, HawkEye will leverages SA Photonics expertise in warfighter body worn equipment and ground troop personal ...

Vadum will develop and demonstrate a software tool for rapid, accurate matching of time-series data to a previously collected database. The Clustered, Shingled Hashing of Random Projections (C-SHARP) tool maps a library of time series data to a compact database of fingerprints. The tool enables efficient queries for matches to a new time series by identifying fingerprint similarity. To support dif ...

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 ...

NGA seeks a solution to provide highly accurate foundation data of buildings, similar features, and linear structures by conflating information from multiple images and contributed content. Our solution “AMCON Geo” (Automated Multi-source Conflation, Geospatial) is a framework for combining multiple sources together to improve overall relative and absolute accuracies of the data, and increase ...

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 ...

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 ...