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The Award database is continually updated throughout the year. As a result, data for FY23 is not expected to be complete until September, 2024.
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SBC: Empower Semiconductor Incorporated Topic: DEFOA0001736
Empower Semiconductor has developed a resonant integrated voltage regulator (IVR) technology that can dramatically improve the energy efficiency of any digital CMOS IC. As Moore’s law has advanced, the plexity and power needs of digital ICs has grown dramatically. The voltages required by these ICs have lowered and the resulting voltage accuracy needs have become more stringent. Existing voltage ...SBIR Phase I 2018 Department of EnergyARPA-E
SBC: MATRIX SENSORS INC. Topic: DEFOA0001738
"We propose to develop a stable, low-cost, low power CO2 sensor module that meets the requirements of the ARPA-E SENSORS FOA, namely, 30 ppm precision over a dynamic range of 400 ppm to 2000 ppm with 10 ppm drift per year. Existing optical non-dispersive infrared (NDIR) CO2 sensors simply cannot scale to the cost and power requirements of the FOA. We therefore propose a solid state architecture ...SBIR Phase I 2018 Department of EnergyARPA-E
SBC: Vaporsens, Inc. Topic: HSB0181001
Drug overdose is now the leading cause of death for Americans under 50 years old, with fentanyl claiming more lives than any other drug.Alarmingly, the problem is increasing, with fentanyl overdoses claiming nearly twice as many lives in 2016 compared to 2015.In addition to users, first responders are at risk for coming into contact with fentanyl as they perform their duties.Fentanyl is extremely ...SBIR Phase I 2018 Department of Homeland Security
SBC: Physical Optics Corporation Topic: HSB0181003
To address the DHS need to rapidly detect radio interference of critical radio frequency (RF) communications channels utilized by first responders, Physical Optics Corporation (POC) proposes to develop a new Miniature Intelligent Spectral Analyzer (MISCAN) device based on a combination of commercial off-the-shelf (COTS) electronic components in a custom software-defined configuration along with in ...SBIR Phase I 2018 Department of Homeland Security
SBC: RAM LABORATORIES Topic: HSB0181008
As Internet of Things (IoT) and mobile devices become increasingly popular and widely used, the security of the firmware running on these devices is paramount.However, due to the lack of an efficient and scalable analysis framework, combined with the increasing pressure to get products to market as quickly as possible, the software running on these devices is never properly checked for security vu ...SBIR Phase I 2018 Department of Homeland Security
SBC: TOYON RESEARCH CORPORATION Topic: HSB0181002
A majority of U.S. adults own a cell phone and are inclined to use it in emergency situations to call for assistance. Unfortunately, in areas where the density of cell towers is low, such as in rural and off-shore environments, the ability of the wireless network to geolocate the origin of the wireless signal is poor to non-existent. Under the proposed effort, Toyon Research Corporation will devel ...SBIR Phase I 2018 Department of Homeland Security
SBC: Physical Optics Corporation Topic: HSB0181002
To address the Department of Homeland Security (DHS) need for a cell phone location finder for maritime and remote search and rescue (SAR), Physical Optics Corporation (POC) proposes to develop a new REmote Phone Locator for Improved Emergency Rescue (REPLIER). REPLIER leverages novel techniques recently developed at POC to extend the range of cellular communications and integrate commercial cellu ...SBIR Phase I 2018 Department of Homeland Security
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: 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
SBC: TOYON RESEARCH CORPORATION Topic: NGA172002
Toyon Research Corporation proposes to research and develop algorithms for low-shot object detection, adapting popular techniques to address the complexities inherent in ATR for remote sensing. Traditional object detection algorithms rely on large corpora of data which may not be available for more exotic targets (such as foreign military assets), and therefore, traditional Convolutional Neural Ne ...SBIR Phase I 2018 Department of DefenseNational Geospatial-Intelligence Agency