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This Government Contract opportunity was posted on February 15, 2012. The submission period has ended. Browse the details below for market research, or find similar active opportunities.

BAYESIAN STATISTICAL METHODS FOR FORWARD LOOKING SONAR APPLICATIONS

Awarded
11-005Federal

Contract Overview

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Under solicitation number 11-005, ARL UT is tasked with developing Bayesian statistical methods for forward looking sonar applications. The primary objective of the project is to assemble a representative set of ahead-looking sonar data that incorporates various complex features known to hinder image interpretation. To address these challenges, ARL UT will implement a series of image processing algorithms derived from established literature. These technical approaches will specifically focus on sub-space modeling, Bayesian dictionary learning, and compressed sensing to improve the clarity and analysis of sonar imagery.

General Info

Agency

N/A

Contract Value

$3,187,205

NAICS

541712 - Research and Development in the Physical, Engineering, and Life Sciences (except Biotechnology)

Place of Performance

MA, USA

Set-Aside

NONE

Awardee

APTIMA INC

Award Issued Date

Documents

0

No documents available

Documents will appear here when they are available.

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Timeline

1 update
PhaseAwarded
Posted

Sources Sought

Notice updated

The response deadline was removed. The notice description changed.

Awarded

Contract was awarded

Submission Closed

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Organization & Contact Information

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AgencyN/A
Contacts2 people available
OfficeN/A
Organization / Agency
N/A
Office AddressN/A
Contacts
Frank KennedyContract Specialist
Phillip EisenhaurContract Specialist

Full Description

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ARL UT will assemble a representative set of ahead-looking sonar data that contains various features that make interpretation of images difficult. ARL UT will implement an initial set of image processing algorithms taken from the literature on compressed sensing, Bayesian dictionary learning, and sub-space modeling.

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