Award Data

Traditional active 3D imaging systems, such as airborne and terrestrial lidar scanners, use a transmitter and receiver typically co-located on the same platform and connected in synchronous communications. However, recent advances in laser, detector, and airborne systems technology have opened the door to smaller, higher-performance and significantly lower-cost airborne lidar systems in which it i ...

NLP pipelines available today are getting robust for general language modeling purposes. But domain-specific data, abbreviations and lingos, and text about time or space still need a lot of tuning and training that are well beyond application of standard tool sets. Deep learning for recommendation engines is quite new, and all recommender systems, in particular for specially trained users, tend to ...

Vadum will develop a deep learning-based computer vision technique to automatically and accurately estimate the number of objects in a synthetic aperture radar (SAR) image. The technique learns on key features of SAR and optical images while being resilient to a wide range of SAR image resolutions, collection geometries and object poses. The analysis architecture is extensible to images collected ...

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 ...

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 ...

Passive microwave sensors aboard satellites provide valuable information regarding weather conditions by measuring atmospheric attenuation over a broad range of frequencies from 0-200 GHz. Additional ground-based sensors are desirable to provide complementary upward looking measurements that can be used to refine existing attenuation models. Operating over such a large bandwidth, however, places ...