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Deep Learning with Whole-Scene Contextual Reasoning for Target Characterization
Award Information
Agency: Department of Defense
Branch: Missile Defense Agency
Contract: HQ0147-17-C-7111
Agency Tracking Number: B2-2503
Amount:
$999,947.00
Phase:
Phase II
Program:
STTR
Solicitation Topic Code:
MDA15-T001
Solicitation Number:
2015.0
Timeline
Solicitation Year:
2015
Award Year:
2017
Award Start Date (Proposal Award Date):
2017-08-09
Award End Date (Contract End Date):
2019-08-09
Small Business Information
20532 El Toro Rd Ste 303
Mission Viejo, CA
92692
United States
DUNS:
825470987
HUBZone Owned:
No
Woman Owned:
No
Socially and Economically Disadvantaged:
No
Principal Investigator
Name: Rich Wolf
Phone: (949) 716-4290
Email: rwolf@exoanalytic.com
Phone: (949) 716-4290
Email: rwolf@exoanalytic.com
Business Contact
Name: Holly Bertrand
Phone: (949) 716-4290
Email: bertrand@exoanalytic.com
Phone: (949) 716-4290
Email: bertrand@exoanalytic.com
Research Institution
Name: T2I Research
Contact: Bruce D'Ambrosio
Phone: (541) 829-6000
Type: Domestic Nonprofit Research Organization
Contact: Bruce D'Ambrosio
Phone: (541) 829-6000
Type: Domestic Nonprofit Research Organization
Abstract
ExoAnalytic Solutions is developing DEEPR (Deep Learning with Whole-Scene Contextual Reasoning for Object Characterization), an advanced multi-sensor multi-object classifier for integrated object characterization. The overall objective of DEEPR is to develop a suite of advanced, novel techniques that combine innovative advances in deep, hierarchical machine learning together with recurrent Deep Learning Neural Network (DNN) methods for sensor fusion, along with Dynamic and Multi-Entity Bayesian Networks (DBNs and MEBNs) for whole-scene and contextual reasoning. Approved for Public Release | 17-MDA-9219 (31 May 17)
* Information listed above is at the time of submission. *
