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Comprehensible Descriptions for Fast Processing of Image Data

Award Information
Agency: Department of Defense
Branch: Missile Defense Agency
Contract: N/A
Agency Tracking Number: 32065
Amount: $500,000.00
Phase: Phase II
Program: SBIR
Solicitation Topic Code: N/A
Solicitation Number: N/A
Timeline
Solicitation Year: N/A
Award Year: 1997
Award Start Date (Proposal Award Date): N/A
Award End Date (Contract End Date): N/A
Small Business Information
8260 Greensboro Drive, Suite 255
Mclean, VA 22102
United States
DUNS: N/A
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Jerzy Bala
 (703) 917-0880
Business Contact
Phone: () -
Research Institution
N/A
Abstract

The proposed effort will apply advanced methods of hybrid learning to problems of detection and identification of sensory events (e.g., boost phase evens). Our approach aims at building a vision system capable of hybrid learning, in which symbolic (rule-based) and subsymbolic (neural network) strategies are integrated to achieve high efficiency and accuracy both in learning human comprehensible sensory descriptions and in employing them for recognition. The proposed approach has several advantages: it can be easily modified and applied to new problems (due to learning) it has fast recognition rates (due to parallel architecture), and its recognition algorithm is easy to understand by a human operator (due to the underlying symbolic knowledge representation).

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

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