• Login
    JavaScript is disabled for your browser. Some features of this site may not work without it.
    Automatic large-scale classification of bird sounds is strongly improved by unsupervised feature learning 
    •   QMRO Home
    • School of Electronic Engineering and Computer Science
    • Centre for Digital Music (C4DM)
    • Automatic large-scale classification of bird sounds is strongly improved by unsupervised feature learning
    •   QMRO Home
    • School of Electronic Engineering and Computer Science
    • Centre for Digital Music (C4DM)
    • Automatic large-scale classification of bird sounds is strongly improved by unsupervised feature learning
    ‌
    ‌

    Browse

    All of QMROCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsThis CollectionBy Issue DateAuthorsTitlesSubjects
    ‌
    ‌

    Administrators only

    Login
    ‌
    ‌

    Statistics

    Most Popular ItemsStatistics by CountryMost Popular Authors

    Automatic large-scale classification of bird sounds is strongly improved by unsupervised feature learning

    View/Open
    Published version (4.072Mb)
    Volume
    2
    DOI
    10.7717/peerj.488
    Journal
    PEERJ
    ISSN
    2167-8359
    Metadata
    Show full item record
    Authors
    Stowell, D; Plumbley, MD
    URI
    http://qmro.qmul.ac.uk/xmlui/handle/123456789/7662
    Collections
    • Centre for Digital Music (C4DM) [210]
    Twitter iconFollow QMUL on Twitter
    Twitter iconFollow QM Research
    Online on twitter
    Facebook iconLike us on Facebook
    • Site Map
    • Privacy and cookies
    • Disclaimer
    • Accessibility
    • Contacts
    • Intranet
    • Current students

    Modern Slavery Statement

    Queen Mary University of London
    Mile End Road
    London E1 4NS
    Tel: +44 (0)20 7882 5555

    © Queen Mary University of London.