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Innovative Concepts for Automated Target Recognition Using Artificial Neural…

Award Information

Agency:
Department of Defense 		Branch:
Defense Advanced Research Projects Agency 		Award ID:
28650 		Program Year/Program:
1995 / SBIR
Agency Tracking Number:
28650 		Solicitation Year:
N/A 		Solicitation Topic Code:
N/A 		Solicitation Number:
N/A
Small Business Information
AEROTECH ENGINEERING & RESEARCH CORP.
3115 W 6th Street Lawrence, KS 66049 0604
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Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No
 
Phase 1
Fiscal Year: 1995
Title: Innovative Concepts for Automated Target Recognition Using Artificial Neural Networks
Agency / Branch: DOD / DARPA
Contract: N/A
Award Amount: $66,642.00
 

Abstract:

The need for an automated target recognition system that can identify a target from a noisy image, irrespective of the target's orientation or size is identified. A novel pulse-coupled neural network is proposed to meet this need. The first step is to capture the image. Next, a neural network is used to determine whether an object of interest exists in the image. Next, another neural network determines the class to which the object belongs. Finally, a third neural netwrok identifies the image within that class. In addition, a system to integrate the developed software for each stage will also be implemented. A work plan and a schedule for Phase I is presented and the expected results are detailed. A general outline of Phase II work is also presented. ANTICIPATED BENEFITS: Development of underground and underwater resource identification systems based on ANNs and fuzzy logic, machine vision for automated manufacturing environments, image analysis systems for the medical fields (CAT-Scans, MRI, X-Rays), ANN-based image analysis methods for law enforcement agencies (finger print analysis, hand-print analysis, DNA analysis).

Principal Investigator:

Swapan Chakrabarti
9138419823

Business Contact:

Small Business Information at Submission:

Aerotech Engineering &
3125 W. 6th Street, Suite C Lawrence, KS 66049

EIN/Tax ID:
DUNS: N/A
Number of Employees:
Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No