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SBC: Achilles Heel Technologies, Inc Topic: HSB0191007
The integration of new cyber technologies in emergency response systems can allow profound improvements in system performance, but also expose the systems to systemic security and privacy risks.Thus, there is a critical need for design-time risk-assessment tools for emergency response systems, which allow evaluation and mitigation of threat impacts across their heterogeneous cyber and physical com ...SBIR Phase I 2019 Department of Homeland Security
SBC: INTELLISENSE SYSTEMS INC Topic: HSB0191003
To address the DHS need for a module that can power/charge and provide effective power management of all on-body electronics including sensors, communications systems, and peripheral devices for all first responder mission areas, Intellisense Systems, Inc. (ISI) proposes to develop a new Power and Rechargeable Battery Interface Smart Module (PRISM). This proposed technology is based on a novel mod ...SBIR Phase I 2019 Department of Homeland Security
SBC: Arete Associates Topic: NGA181008
We propose to build ARGON, the ARet Ground-to-Overhead Network. The network will ingest analyst-supplied ground-level imagery ofobjects and retrieve instances of those objects in overhead collections, providing tips back to the analysts. A proprietary method of trainingthe network, leveraging in-house capabilities, data sources, and tools, will be critical to its success. During Phase I, we will p ...SBIR Phase I 2018 Department of DefenseNational Geospatial-Intelligence Agency
SBC: MAYACHITRA, INC. Topic: NGA181005
Building interpretable, composable autonomous systems requires consideration of uncertainties in the decisions and detections theygenerate. Human analysts need accurate absolute measures of probability to determine how to interpret and use the sometimes noisy resultsof machine learning systems; and composable autonomous systems need to be able to propagate uncertainties so that later reasoningsyst ...SBIR Phase I 2018 Department of DefenseNational Geospatial-Intelligence Agency
SBC: TOYON RESEARCH CORPORATION Topic: NGA181010
The National Geospatial-Intelligence Agency (NGA) ingests and analyzes raw imagery from multiple sources to form actionable intelligenceproducts that can be disseminated across the intelligence community (IC). To effectively meet these demands NGA must continue to improveits automated and semi-automated methods for target detection and classification. Of particular concern is furthering NGA's abil ...SBIR Phase I 2018 Department of DefenseNational Geospatial-Intelligence Agency
SBC: TOYON RESEARCH CORPORATION Topic: NGA181004
Toyon Research Corp. proposes development of a system that automates disaster assessment based on fusion of overhead and ground-basedimages, video, and other data. In Phase I, we will investigate various possible data sources and the benefits of fusing the data in automatedanalysis. We will select and curate data for processing in a Phase I feasibility study. Damage assessment will be performed in ...SBIR Phase I 2018 Department of DefenseNational Geospatial-Intelligence Agency
SBC: TOYON RESEARCH CORPORATION Topic: NGA181006
Toyon Research Corporation proposes to research and develop algorithms for generalized change detection, by leveraging and exploringexisting and proven effective traditional and deep learning methods, with a unique 3D reconstruction component. The vast majority of themassive amounts of imagery data will have small pixel level differences due to a multitude of unimportant changes: minor misregistra ...SBIR Phase I 2018 Department of DefenseNational Geospatial-Intelligence Agency
Hybrid DNN-based Transfer Learning and CNN-based Supervised Learning for Object Recognition in Multi-modal Infrared ImagerySBC: TOYON RESEARCH CORPORATION Topic: 1
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 ...STTR Phase I 2018 Department of DefenseNational Geospatial-Intelligence Agency
SBC: INTELLISENSE SYSTEMS INC Topic: NGA181005
To address the National Geospatial-Intelligence Agency (NGA) need for overhead imagery analysis algorithms that provide uncertaintymeasures for object recognition and aggregation, Intellisense Systems, Inc. (ISS) proposes to develop a new Variational Object Recognition andGrouping Network (VORGNet) system. It is based on the innovation of implementing a Bayesian convolutional neural network (CNN) ...SBIR Phase I 2018 Department of DefenseNational Geospatial-Intelligence Agency
SBC: INTELLISENSE SYSTEMS INC Topic: NGA181004
To address the NGA need for algorithms that fuse observables from over-flight operations and from ground sources to automatically estimatethe degradation of urban environments due to battle damage or natural disasters, Intellisense Systems, Inc. (ISS) proposes to develop a newBayesian Urban Degradation Assessment (BUDA) software system. It is based on the integration of multiple damage assessment ...SBIR Phase I 2018 Department of DefenseNational Geospatial-Intelligence Agency