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Technical Reports


  • @techreport{SMM1998a,
    	vgclass =	{report},
    	vgproject =	{viper,cbir},
    	author =	{David McG. Squire and Wolfgang M\"{u}ller and Henning M\"{u}ller},
    	title =	{Relevance feedback and term weighting schemes for content-based
    image retrieval},
    	number =	{98.05},
    	institution =	{Computer Vision Group,  Computing Centre, University of Geneva},
    	address =	{rue G\'{e}n\'{e}ral Dufour, 24, CH-1211 Gen\`{e}ve, Switzerland},
    	month =	{December},
    	year =	{1998},
    	url =	{/publications/postscript/1998/VGTR98.05_SquireMuellerMueller.pdf},
    	url1 =	{/publications/postscript/1998/},
    	abstract =	{This paper describes the application of techniques derived
    	from text retrieval research to the content-based querying of image
    	databases.  Specifically, the use of inverted files, frequency-based
    	weights and relevance feedback are investigated. The use of inverted
    	files allows very large numbers ($\geq \mathcal{O}(10^4)$) of
    	\emph{possible} features to be used.  since search is limited to the
    	subspace spanned by the features present in the query image(s). A
    	variety of weighting schemes used in text retrieval are employed,
    	yielding different results. We suggest possibles modifications for
    	their use with image databases. The use of relevance feedback was shown
    	to improve the query results significantly, as measured by precision
    	and recall, for all users.},