Decision Learning Algorithm for Acoustic Vessel Classification
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Authors
Meir, Talmor
Tsionskiy, Mikhail
Sutin, Alesander
Salloum, Hady
Subjects
Advisors
Date of Issue
2012-04
Date
2012-04
Publisher
Monterey, California. Naval Postgraduate School
Center for Homeland Defense and Security
Center for Homeland Defense and Security
Language
en_US
Abstract
"Detection, tracking and classifying vessels of all sizes approaching ports and harbors is an imperative aspect to the security of complex maritime systems. This case study is an application of the passive acoustic method for vessel classification. The analysis of noise radiated by passing boats in Hudson River provides sound signatures and specific acoustic features of various boats. The features are then implemented into a decision-making algorithm used for final classification."
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Article
Description
This article appeared in Homeland Security Affairs (April 2012), supplement 4, article 3
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Citation
Homeland Security Affairs (April 2012), supplement 4, article 3
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The copyright of all articles published in Homeland Security Affairs rests with the author[s] of the articles. Any commercial use of Homeland Security Affairs or the articles published herein is expressly prohibited without the written consent of the copyright holder. Anyone can copy, distribute, or reuse these articles as long as the author and original source are properly cited.