Supervised Learning for Automated Detection of Events
Barron Associates proposes to develop and demonstrate algorithms for detecting events involving one or more objects in a sensor data stream and mechanisms for post-deployment training of those algorithms by analysts. The algorithm training approach will be highly efficient, requiring minimal interaction with analysts, who need only provide an example of the desired event and possibly answer a small number of questions clarifying their intent. The resulting system will allow analysts to save and share event definitions, will run in real-time, and will be built around a service oriented architecture for ease of integration into existing and forthcoming systems. The project will leverage significant existing capabilities in the area of automated behavior analysis developed by Barron Associates.
Small Business Information at Submission:
Senior Research Scientist
Barron Associates, Inc.
1410 Sachem Place Suite 202 Charlottesville, VA -
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