REAL-TIME MODEL-BASED OBJECT RECOGNITION USING A COMBINED NEURAL NETWORK/EXPERT SYSTEM

Award Information
Agency: Department of Defense
Branch: Navy
Contract: N/A
Agency Tracking Number: 9037
Amount: $280,000.00
Phase: Phase II
Program: SBIR
Awards Year: 1989
Solicitation Year: N/A
Solicitation Topic Code: N/A
Solicitation Number: N/A
Small Business Information
Reshet Inc.
314 - N 32nd St, Philadelphia, PA, 19104
DUNS: N/A
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Dr James Eilbert
 (215) 222-9117
Business Contact
Phone: () -
Research Institution
N/A
Abstract
THIS PROPOSAL IS MOTIVATED BY THE COMPLEMENTARY CAPABILITIES OF EXPERT SYSTEM AND NEURAL NETWORK (NN) TECHNOLOGIES, AND BY THE POTENTIAL FOR A COMBINED SYSTEM TO PERFORM MORE EFFECTIVELY THAN EITHER ALONE. THE LOCAL, BOTTOM-UP APPROACH TO VISION CANNOT DEAL WITH THE NOISE AND THE ON-GOING PRODUCTION OF NOVELTY IN REAL VISUAL SCENES, WHILE EXPERT SYSTEM APPROACHES ARE TOO BRITTLE AND SLOW TO DO REAL-TIME IMAGE PROCESSING. WE BELIEVE THE COMBINED NN/EXPERT SYSTEM ARCHITECTURE IN THIS PROPOSAL WILL OVERCOME MANY OF THE PROBLEMS WITH PREVIOUS APPROACHES. THE PROPOSED PROJECT HAS 2 PRIMARY GOALS: 1) TO CONSTRUCT A COMPUTER APPLICATION THAT COMBINES A NEURAL NETWORK (NN) COMPONENT AND AN EXPERT SYSTEM COMPONENT IN A WAY THAT ENHANCES THE PERFORMANCE OF EACH; 2) USE THE SYSTEM TO CREATE FASTER MORE FLEXIBLE SOLUTIONS TO EXPERT LEVEL PROBLEMS IN VISION.

* information listed above is at the time of submission.

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