Palmprint recognition based on unsupervised subspace analysis
- Author
- GUIYU FENG1 ; DEWEN HU1 ; MING LI1 ; ZONGTAN ZHOU1
[1] Department of Automatic Control, College of Mechatronics and Automation, National University of Defense Technology, Changsha, Hunan, 410073, China - Conference title
- Advances in natural computation (Changsha, 27-29 August 2005)
- Conference name
- ICNC : international conference on advances in natural computation (1 ; Changsha 2005-08-27)
- Author (monograph)
- Wang Lipo (Editor); Chen Ke (Editor); Ong Yew Soon (Editor)
- Source
Lecture notes in computer science. 2005 ; 3Vol ; Part 1, 675-678 ; ref : 11 ref
- ISSN
- 0302-9743
- ISBN
- 3-540-28323-4
- Scientific domain
- Computer science
- Publisher
- Springer, Berlin
- Publication country
- Germany
- Document type
- Conference Paper
- Language
- English
- Keyword (fr)
- Analyse composante indépendante Analyse composante principale Classification Espace vectoriel Extraction caractéristique Extraction forme Reconnaissance forme
- Keyword (en)
- Independent component analysis Principal component analysis Classification Vector space Feature extraction Pattern extraction Pattern recognition
- Keyword (es)
- Analisis componente independiente Análisis componente principal Clasificación Espacio vectorial Extracción forma Reconocimiento patrón
- Classification
- Pascal
- 001 Exact sciences and technology / 001D Applied sciences / 001D02 Computer science; control theory; systems / 001D02C Artificial intelligence
- Discipline
- Computer science : theoretical automation and systems
- Origin
- Inist-CNRS
- Database
- PASCAL
- INIST identifier
- 17135849
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
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