Ir al contenido (pulsa Retorno)

Universitat Politècnica de Catalunya

    • Català
    • Castellano
    • English
    • LoginRegisterLog in (no UPC users)
  • mailContact Us
  • world English 
    • Català
    • Castellano
    • English
  • userLogin   
      LoginRegisterLog in (no UPC users)

UPCommons. Global access to UPC knowledge

57.066 UPC E-Prints
You are here:
View Item 
  •   DSpace Home
  • E-prints
  • Grups de recerca
  • LAB - Laboratori d'Aplicacions Bioacústiques
  • Ponències/Comunicacions de congressos
  • View Item
  •   DSpace Home
  • E-prints
  • Grups de recerca
  • LAB - Laboratori d'Aplicacions Bioacústiques
  • Ponències/Comunicacions de congressos
  • View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.

A novel approach to real-time range estimation of underwater acoustic sources using supervised machine learning

Thumbnail
View/Open
OCEANSAberdeen2017_Ludwig.pdf (1,634Mb)
Share:
 
 
10.1109/OCEANSE.2017.8084914
 
  View Usage Statistics
Cita com:
hdl:2117/114690

Show full item record
Houégnigan, LudwigMés informacióMés informacióMés informació
Safari, PooyanMés informació
Nadeu Camprubí, ClimentMés informacióMés informacióMés informació
Van der Schaar, Mike Connor Roger MalcolmMés informacióMés informació
André, MichelMés informacióMés informacióMés informació
Document typeConference lecture
Defense date2017
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Rights accessOpen Access
All rights reserved. This work is protected by the corresponding intellectual and industrial property rights. Without prejudice to any existing legal exemptions, reproduction, distribution, public communication or transformation of this work are prohibited without permission of the copyright holder
ProjectTECNOLOGIAS DE APRENDIZAJE PROFUNDO APLICADAS AL PROCESADO DE VOZ Y AUDIO (MINECO-TEC2015-69266-P)
Abstract
The proposed paper introduces a novel method for range estimation of acoustic sources, both cetaceans and industrial sources, in deep sea environments using supervised learning with neural networks in the contex of a single sensor, a compact array, or a small aperture towed array. The presented results have potential both for industrial impact and for the conservation and density estimation of cetaceans. With an average error of 4.3% for ranges up to 8 kilometers and typically below 300 meters, those results are challenging and to our knowledge they are unprecedented for an automated real-time solution.
Description
© 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
CitationHouegnigan, L., Safari, P., Nadeu, C., Van Der Schaar, M., Andre, M. A novel approach to real-time range estimation of underwater acoustic sources using supervised machine learning. A: OCEANS IEEE/MTS Aberdeen. "OCEANS 2017 - Aberdeen: 19-22 June 2017". Institute of Electrical and Electronics Engineers (IEEE), 2017, p. 1-5. 
URIhttp://hdl.handle.net/2117/114690
DOI10.1109/OCEANSE.2017.8084914
ISBN978-1-5090-5278-3
Publisher versionhttp://ieeexplore.ieee.org/document/8084914/
Collections
  • LAB - Laboratori d'Aplicacions Bioacústiques - Ponències/Comunicacions de congressos [13]
  • Centre Tecnològic de Vilanova i la Geltrú - Ponències/Comunicacions de congressos [26]
  • VEU - Grup de Tractament de la Parla - Ponències/Comunicacions de congressos [436]
  • Departament de Teoria del Senyal i Comunicacions - Ponències/Comunicacions de congressos [3.190]
Share:
 
  View Usage Statistics

Show full item record

FilesDescriptionSizeFormatView
OCEANSAberdeen2017_Ludwig.pdf1,634MbPDFView/Open

Browse

This CollectionBy Issue DateAuthorsOther contributionsTitlesSubjectsThis repositoryCommunities & CollectionsBy Issue DateAuthorsOther contributionsTitlesSubjects

© UPC Obrir en finestra nova . Servei de Biblioteques, Publicacions i Arxius

info.biblioteques@upc.edu

  • About This Repository
  • Contact Us
  • Send Feedback
  • Inici de la pàgina