This National Science Foundation Project Grant under the Computer and Information Science and Engineering program ($149,995) supports research at Arizona State University from April 2023 through March 2026 to develop a generalizable motion field estimator using neural networks for enhanced long-range imaging computer vision applications. The award aims to address deteriorated performance of data-driven computer vision approaches when images are captured from long distances, such as with unmanned...
The Johns Hopkins University received a $500,000 Project Grant award from the National Science Foundation Division of Electrical, Communications and Cyber Systems on March 15, 2021 to support research titled "CAREER: SEEING THROUGH ATMOSPHERIC TURBULENCE: IMAGE RESTORATION AND UNDERSTANDING USING DEEP CONVOLUTIONAL NEURAL NETWORKS." The research is funded through the NSF's Engineering program (CFDA #47.041), which aims to improve quality of life and economic strength through...
This $499,495 National Science Foundation project grant supports the development of computational imaging solutions to facilitate underwater robotic tasks through September 2024. Funded under the NSF's Computer and Information Science and Engineering program (CFDA 47.070), the grantee George Mason University will develop a novel angularly sampled imaging system and algorithms to analyze nonlinear light transport in water, model underwater surface reflectance, and reconstruct three-dimensional...
This two-year, $255,000 Project Grant from the National Science Foundation's Geosciences program (CFDA 47.050) will support the development of a new remote sensing technique for measuring seismic waves at Michigan Technological University. The researchers will enhance the Moiré technique, which images patterns from differential motion between grids, by placing one grid on a remote location using an unmanned aerial vehicle and the other within a base telescope. This will enable measurement of...
This $204,884 Project Grant award from the National Science Foundation (NSF) Directorate for Mathematical and Physical Sciences (CFDA 47.049) supports research by Towson University to study various subgrid scale turbulence models and their connections to the Navier-Stokes equations. The research aims to explore the mathematical properties of these turbulence models, apply data assimilation algorithms, and leverage deep learning methods for parameter estimation. Key focus areas include...
George Mason University was awarded a $293,426 Project Grant from the National Science Foundation Office of Advanced Cyberinfrastructure on June 15, 2022 to complete the project by May 31, 2027. The grant was awarded under the Computer and Information Science and Engineering program (CFDA #47.070), which supports investigator-initiated research and education in computing, communications, and information science and engineering. Specifically, the grant will fund the development of...
This $499,624 National Science Foundation project grant supports research at the University of Pittsburgh to develop physics-guided machine learning methods for turbulent flow simulation. Funded under the NSF's Computer and Information Science and Engineering program (CFDA 47.070), the three-year award aims to advance computational fluid dynamics capabilities. Specifically, the university researchers will create a new deep learning model incorporating physical constraints to reconstruct...
George Mason University was awarded a $325,933 project grant from the National Science Foundation Division of Information and Intelligent Systems. The grant was awarded under the Computer and Information Science and Engineering program (CFDA 47.070) to support a three-year collaborative research project titled "Principled Uncertainty Quantification in Deep Learning Models for Time Series Analysis" from October 1, 2021 through September 30, 2024. The project aims to advance the...
This $1,200,000 Project Grant was awarded on August 15, 2023 by the National Science Foundation (NSF) Division of Information and Intelligent Systems under the Computer and Information Science and Engineering program (CFDA 47.070). The grant supports research at The Pennsylvania State University (Penn State) to develop computer vision algorithms that can accurately estimate biomechanical data like body pose, motion, and forces from video data alone. This will enable the observation of human...
This three-year, $309,811 project grant from the National Science Foundation's Engineering program (CFDA 47.041) will fund research at The Trustees of the Stevens Institute of Technology to develop techniques for improving the resilience of vision-guided unmanned aerial vehicles and other mobile robotic technologies against cyberattacks. The research aims to advance a framework for detecting and responding to stealthy attacks that simultaneously target mission planning, control, perception,...