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The Award database is continually updated throughout the year. As a result, data for FY22 is not expected to be complete until September, 2023.
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A data dictionary and additional information is located on the Data Resource Page. Files are refreshed monthly.
Reverberation Mitigation of SpeechSBC: Minerva Systems & Technologies, LLC Topic: AF15AT17
Automatic speech recognition (ASR) technology is in wide use today and has been successfully integrated into a number of applications. Although there are also many potential applications for automatic speaker identification (SID), SID accuracy rates are generally not sufficient for widespread use in practical applications. For high accuracy ASR and SID, the microphone must be located near the talk ...STTR Phase II 2016 Department of DefenseAir Force
Small Sample Size Semi-Supervised Feature Clustering for Detection and Classification of Objects and Activities in Still and Motion Multi-spectral ImagerySBC: TOYON RESEARCH CORPORATION Topic: AF15AT35
Toyon Research Corp. and the Penn State Univ. propose research and development of innovative algorithms for classifying objects and activities observed in high-dimensional data extracted from multi-sensor motion imagery. The proposed algorithms include novel feature clustering techniques to enable effective characterization of intra-class and inter-class appearance variations in datasets containin ...STTR Phase II 2016 Department of DefenseAir Force
Hypersonic Experimental Aerothermoelastic Test (HEAT)SBC: Global Aerospace Corporation Topic: AF16AT24
The U.S. Air Force is interested in developing hypersonic vehicles including reusable transport aircraft, cruise missiles, and unmanned systems. Hypersonic flight regimes result in multifaceted and very difficult design challenges that can be encapsulated into an aerothermoelastic problem, which is a complex interaction of structural, thermal, and aerodynamic mechanisms. When a flexible structural ...STTR Phase II 2018 Department of DefenseAir Force
ENHANCING MOTION IMAGERY CLASSIFIERS BY PRINCIPAL COMPONENT FEATURE CLUSTERINGSBC: LONGSHORTWAY INC. Topic: AF15AT35
LongShortWay Inc. and Northeastern University propose a family of feature reduction and ensemble classifier methods based on Principal Component and Dynamic Logic feature clustering algorithms. New methods combine feature clustering with non-linear feature reduction via manifold learning, and bagging, boosting, and stacking ensemble algorithms.STTR Phase II 2016 Department of DefenseAir Force