Award Data

The team of Signature Research, Inc. and Michigan Technological University will develop and demonstrate methods and metrics to evaluate the performance of machine learning-based computer vision algorithms with low numbers of samples of labeled EO imagery. We will use the existing xView panchromatic dataset to demonstrate a proof-of-concept set of tools. If successful, in Phase II, we will extend t ...

Signature Research, Inc. (SGR) and Michigan Technological University (MTU) propose a Phase I STTR effort to develop a learning algorithm which exploits the spatio-spectral characteristics inherent within IR imagery and motion imagery.Our archive of modelled and labeled data sets will allow our team to thoroughly capture the variable elements that will drive machine learning performance.The overall ...

In a pandemic or exposure to weaponized Marburg virus the morbidity, mortality and social unrest that will ensue before vaccines orMilitary operating on foreign soil as well as to the population of the US Homeland. Practically all threat agents of biological origin (except forcertain non-proteinaceous toxins, typically produced by marine organisms and fungi) have their structure and vital function ...

Low-shot objection recognition has become an area of active research in recent years, with advances dramatically improving performance when only a few samples are available, nominally fewer than 20. These technologies are a focus of the intelligence community (IC) because this challenge pertains to many intelligence problems, e.g., objects of interest are rare due to their use, sensitive nature, ...

In resource limited settings, rapid and accurate diagnosis of infections is critical for managing potential exposures to highly virulent pathogens,whether occurring from an act of bioterrorism or a natural event. This is especially important for hard to detect intracellular bacterial andalphavirus infections, that overlap symptomatically and often treated empirically due to a lack of reliable and ...