Recognition and visualization of music sequences using self-organizing feature maps

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 6359 LNAI, Issue , 2010, Pages 160-167

  Hein, Tobias ^a   Kramer, Oliver ^b  

^a TU DORTMUND UNIVERSITY   (Germany)

^b INTERNATIONAL COMPUTER SCIENCE INSTITUTE   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ASSISTING TOOLS; AUTOMATIC DISCOVERY; EXPERIMENTAL ANALYSIS; FAST FORWARD; FEATURE VECTORS; HIGH-DIMENSIONAL; HUMAN ANALYSIS; MOTIF SEARCH; MUSIC COMPOSITION; MUSIC DATA; PRE-PROCESSING STEP; SELF-ORGANIZING FEATURE MAP; SONG STRUCTURE; LOW DIMENSIONAL;

ARTIFICIAL INTELLIGENCE; CONFORMAL MAPPING; FEATURE EXTRACTION; POTASSIUM IODIDE; VISUALIZATION; CLASSIFIERS;

SELF ORGANIZING MAPS;

EID: 78349275330     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-16111-7_18     Document Type: Conference Paper

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