Open AccessScene classification in compressed and constrained domain
Author(s) -
Giovanni Maria Farinella,
Sebastiano Battiato
Publication year - 2011
Publication title -
iet computer vision
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.38
H-Index - 37
eISSN - 1751-9640
pISSN - 1751-9632
DOI - 10.1049/iet-cvi.2010.0056
Subject(s) - computer science , exploit , artificial intelligence , classifier (uml) , jpeg , discrete cosine transform , representation (politics) , computer vision , domain (mathematical analysis) , encode , pattern recognition (psychology) , image (mathematics) , mathematics , mathematical analysis , biochemistry , chemistry , computer security , politics , political science , law , gene
Holistic representations of natural scenes are an effective and powerful source of information for semantic classification and analysis of images. Despite the technological hardware and software advances, consumer single-sensor imaging devices technology are quite far from the ability of recognising scenes and/or to exploit the visual content during (or after) acquisition time. The frequency domai...
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