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CONTEXT-DRIVEN LANDMINE DETECTION USING SEMI-SUPERVISED MULTI-TASK LEARNING

Award Information

Agency:
Department of Defense 		Branch:
Army 		Award ID:
97593 		Program Year/Program:
2010 / SBIR
Agency Tracking Number:
A092-078-0679 		Solicitation Year:
N/A 		Solicitation Topic Code:
Army 09-078 		Solicitation Number:
N/A
Small Business Information
Signal Innovations Group, Inc.
4721 Emperor Blvd. Suite 330 Durham, NC -
View profile »
Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No
 
Phase 1
Fiscal Year: 2010
Title: CONTEXT-DRIVEN LANDMINE DETECTION USING SEMI-SUPERVISED MULTI-TASK LEARNING
Agency / Branch: DOD / ARMY
Contract: W15P7T-10-C-S007
Award Amount: $69,982.00
 

Abstract:

The proliferation of landmines continues to be a problem of worldwide humanitarian urgency. While airborne sensors have demonstrated significant utility in covering a wide area at a high stand-off distance, the variety of deployment methods, environments, mine types, and operating conditions continue to pose challenges in the context of landmine detection requirements. In this effort, a context-driven approach to the landmine detection architecture is proposed with a focus on transitioning new mathematical and statistical tools for applied image processing that are highly relevant to addressing landmine detection challenges. We propose a framework that provides: texture-based context for anomaly detection; false alarm reduction through semi-supervised learning and multi-task learning where data associations are learned in the feature space and the classifier parameter space; mine field association through graph-based diffusion; and a mechanism to explicitly incorporate analyst feedback to optimize performance under new operating conditions. Computational efficiency of the underlying methods will aid in pursuing real-time implementation, test and evaluation in Phase II.

Principal Investigator:

Levi Kennedy
Vice President of Engineering
9193233456
lkennedy@siginnovations.com

Business Contact:

David Dye
VP of Operations
9197943322
demetri@solidstateresearch.com
Small Business Information at Submission:

Signal Innovations Group, Inc.
1009 Slater Rd. Suite 200 Durham, NC 27703

EIN/Tax ID: 201104360
DUNS: N/A
Number of Employees:
Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No