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Integration of a Machine-Learning based Threat Identification with VICE

Award Information
Agency: Department of Defense
Branch: Army
Contract: W909MY-21-P-0002
Agency Tracking Number: A201-076-0715
Amount: $111,499.40
Phase: Phase I
Program: SBIR
Solicitation Topic Code: A20-076
Solicitation Number: 20.1
Solicitation Year: 2020
Award Year: 2020
Award Start Date (Proposal Award Date): 2020-06-23
Award End Date (Contract End Date): 2021-04-30
Small Business Information
3741 Plaza Drive
Ann Arbor, MI 48108-1655
United States
DUNS: 197187602
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Charles Cohen
 (734) 668-2567
Business Contact
 Margaret Press
Phone: (734) 668-2567
Research Institution

(VICE) to collect faces and identify them in large photo and video collections.   In the proposed work we will extend this capability to incorporate vehicles, persons, and weapons recognition into the VICE so that people, weapons, and vehicles can be correlated and identify as friend of foe (i.e. non-threat and threat).   Cybernet built for the Army Research Office (and later the Air Force and the Joint IED Organization), a learning-based computer vision system that incorporates (1) hand or manual and machine learning capabilities, (2) truth data collection and processing, (c) location and history retention, and (d) animals and threat recognition learning and automatic tagging.  This system has been applied to generic recognition and tracking of vehicles, person & carried items, generically potential threats, and species of animal for environment reporting and identification counts. Our system includes tools and Machine Learning (ML) methodology (and existing vehicle, person, and carried item recognition codes) that should readily port to the VICE environment for an immediate proof of concept result in Phase I and can be extended through processing and assessment of larger Phase II training sets to continuously improve recognition rates and threat-Identify pairing performance.

* Information listed above is at the time of submission. *

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