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» Learning the Relative Importance of Features in Image Data
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ICPR
2010
IEEE
15 years 2 months ago
User Adaptive Clustering for Large Image Databases
Abstract--Searching large image databases is a time consuming process when done manually. Current CBIR methods mostly rely on training data in specific domains. When source and dom...
Mohammad Mehdi Saboorian, Mansour Jamzad, Hamid R....
WWW
2005
ACM
16 years 5 months ago
Web data cleansing for information retrieval using key resource page selection
With the page explosion of WWW, how to cover more useful information with limited storage and computation resources becomes more and more important in web IR research. Using web p...
Yiqun Liu, Canhui Wang, Min Zhang, Shaoping Ma
RAS
2008
112views more  RAS 2008»
15 years 3 months ago
Learning and generalising semantic knowledge from object scenes
The robot described in this paper learns words that relate to objects and their attributes and also learns concepts, which may be recursive, that involve relationships between sev...
Claire D'Este, Claude Sammut
ICASSP
2011
IEEE
14 years 8 months ago
Denoising sparse noise via online dictionary learning
The idea of learning overcomplete dictionaries based on the paradigm of compressive sensing has found numerous applications, among which image denoising is considered one of the m...
Anoop Cherian, Suvrit Sra, Nikolaos Papanikolopoul...
LWA
2007
15 years 5 months ago
Position Paper: Ontology Learning from Folksonomies
The emergence of collaborative tagging systems with their underlying flat and uncontrolled resource organization paradigm has led to a large number of research activities focussi...
Dominik Benz, Andreas Hotho