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Award Data

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The Award database is continually updated throughout the year. As a result, data for FY20 is not expected to be complete until September, 2021.

  1. Hybrid DNN-based Transfer Learning and CNN-based Supervised Learning for Object Recognition in Multi-modal Infrared Imagery

    SBC: 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
  2. Algorithms for Look-down Infrared Target Exploitation

    SBC: Signature Research, Inc.            Topic: 1

    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 ...

    STTR Phase I 2018 Department of DefenseNational Geospatial-Intelligence Agency
  3. Brain Targeting Nanoparticle for Drug Delivery in Traumatic Brain Injury

    SBC: Weinberg Medical Physics, Inc.            Topic: DHA18A001

    There is an urgent need to bypass or cross the blood brain barrier (BBB) to deliver drugs for TBI treatment. This project aims to develop targted intranasally delivered, magnetically propulsed, and targted nanoparticles for traumatic brain injury (TBI). In Phase I, we will demonstrate the design, fabrication, and in vitro characterization of proposed drug laden magnetic nanoparticles as well as co ...

    STTR Phase I 2018 Department of DefenseDefense Health Program
  4. System for Nighttime and Low-Light Face Recognition

    SBC: MUKH Technologies LLC            Topic: SOCOM18A001

    Recognizing faces in low-light and nighttime conditions is a challenging problem due to the noisy and poor quality nature of the images.Thermal imaging is often used to obtain facial biometric in such conditions. Thermal face images, while having a strong signature at nighttime, are not typically maintained in biometric-enabled watch lists and so must be compared with visible-light face images to ...

    STTR Phase I 2018 Department of DefenseSpecial Operations Command
  5. Human Performance Optimization: Ketone Esters for Optimization of Operator Performance in Hypoxia

    SBC: HVMN Inc.            Topic: SOCOM17C001

    In the setting of altitude-induced hypoxia, operator cognitive capacity degrades and can compromise both individual and team performance. This degradation is linked to falling brain energy (ATP) levels and an increased reliance on anaerobic energy production from glucose. Ketone bodies are the evolutionary alternative substrate to glucose for brain metabolic requirements; previous studies have sho ...

    STTR Phase I 2018 Department of DefenseSpecial Operations Command
  6. Griffon Test Suite

    SBC: Soar Technology, Inc.            Topic: DHA17C001

    In this proposal we support the development of a hypoxia test battery by designing and developing a domain general tool suite for processing, synchronizing, and evaluating data from cognitive, behavioral, and physiological measures.The proposed Griffon Tool Suite addresses many of the practical requirements demanded by a flexible test battery. The effort falls into three major thrusts.First, we pr ...

    STTR Phase I 2018 Department of DefenseDefense Health Program
  7. Handoff Training for Combat Casualty Care (HTC3) Framework

    SBC: Perceptronics Solutions, Inc.            Topic: DHA17B001

    This proposal is to develop a Handoff Training for Combat Casualty Care (HTC3) Framework.Training is the crux of the handoff problem today. Patient handoffs are a crucial part of casualty care, both in military and civilian environments; and today handoffs are being performed in less than optimal fashion, with ineffective communications accounting for 80% of the handoff errors. Our new HTC3 Framew ...

    STTR Phase I 2018 Department of DefenseDefense Health Program
  8. Combat Casualty Handoff Automated Trainer (CCHAT)

    SBC: Soar Technology, Inc.            Topic: DHA17B001

    Combat casualty handoffs are critical communication moments during which responsibility for the patient and important casualty information is transferred between providers. The nature of these handoffs requires specialized training, for which no standardized framework currently exists. The proposed effort aims to develop a capability, compatible with current DoD systems, that provides caregivers w ...

    STTR Phase I 2018 Department of DefenseDefense Health Program
  9. CCHAT Handoff Protocol

    SBC: Soar Technology, Inc.            Topic: DHA17B002

    Research has identified that handoffs are particularly important communication processes, during which communication error can lead to patient safety situations. Organizations have created standard practices and training materials to encourage teamwork communication for handoffs, however these do not necessarily capture the needs of military medicine of combat casualty care. Combat casualty handof ...

    STTR Phase I 2018 Department of DefenseDefense Health Program
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