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 ...

Deep Neural Networks have become ubiquitous in the modern analysis of voluminous datasets with geometric symmetries. In the field of Particle Physics, experiments such as DUNE require the detection of particle signatures interacting within the detector, with analyses of over a billion 3D event images per channel each year; with typical setups containing over 150,000 different channels.  In an ...

On this effort Toyon Research Corp. and The Pennsylvania State University are developing deep learning-based algorithms for object recognition and new class discovery in look-down infrared (IR) imagery. Our approach involves the development of a hybrid classifier that exploits both transfer learning and semi-supervised paradigms in order to maintain good generalization accuracy, especially when li ...

The broader impact/commercial potential of this Small Business Technology Transfer (STTR) Phase I project is to open new orbital flight regimes to CubeSat and microsatellite vehicles. Vehicles of these size classes are currently constrained by the lack of suitable propulsion options or additional regulatory burdens that most propulsion systems levy on rideshare vehicles. Most small satellites in L ...

The broader impact / commercial potential of this Small Business Technology Transfer (STTR) Phase I project is to enable electrification of remote oil & gas processes to reduce methane emissions, improve on-site safety, and provide leak-detection and monitoring capabilities. This will be achieved by developing a robust, efficient, small-scale power generator capable of converting on-site fuel to e ...

The broader/commercial impact of this STTR Phase 1 project will develop an automated system that significantly increases the speed, reliability, and accuracy of disease severity assessment in ulcerative colitis (UC) patients. This lifelong debilitating disease impacts almost 1 M US patients, and developing effective treatments requires accurate, reliable, and timely scoring. Currently, the FDA-app ...

The broader impact/commercial potential of this Small Business Technology Transfer (STTR) Phase I project is to enable the discovery of new therapeutics targeting G protein-coupled receptors (GCPRs). GPCRs are expressed in nearly every organ system, are accessible due to their location on the membrane and potential to elicit almost every signaling pathway. Drugs targeting GPCRs make up 35% of all ...

The broader impact/commercial potential of the proposed STTR Phase I project is to build a non-invasive medical device for fetal health monitoring to assist obstetricians in avoiding unnecessary cesarean-section surgeries (C-Sections). Despite significant cost and clear evidence of health risks associated with C-Sections, many infants are delivered via C-Sections. The high C-section rate and the a ...

The broader impact commercial potential of this Small Business Technology Transfer (STTR) Phase I project is to improve the accessibility of eye health care. Glaucoma is a major cause of irreversible blindness but can be addressed with early detection, and the prevalence increases with age. However, existing tests can be tiring and difficult and require specialized equipment. This project will adv ...