http://www.cnr.it/ontology/cnr/individuo/prodotto/ID204424
Combining local and global visual feature similarity using a text search engine (Contributo in atti di convegno)
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- Label
- Combining local and global visual feature similarity using a text search engine (Contributo in atti di convegno) (literal)
- Anno
- 2011-01-01T00:00:00+01:00 (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
- 10.1109/CBMI.2011.5972519 (literal)
- Alternative label
Amato G., Bolettieri P., Falchi F., Gennaro C., Rabitti F. (2011)
Combining local and global visual feature similarity using a text search engine
in 9th International Workshop on Content-Based Multimedia Indexing, Madrid, 13-15 June 2011
(literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
- Amato G., Bolettieri P., Falchi F., Gennaro C., Rabitti F. (literal)
- Pagina inizio
- Pagina fine
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#altreInformazioni
- Area di valutazione 01 - Scienze matematiche e informatiche (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#url
- http://dx.doi.org/10.1109/CBMI.2011.5972519 (literal)
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- PuMa (literal)
- Scopu (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
- CNR-ISTI, Pisa, Italy (literal)
- Titolo
- Combining local and global visual feature similarity using a text search engine (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#isbn
- 978-1-61284-432-9 (literal)
- Abstract
- In this paper we propose a novel approach that allows processing image content based queries expressed as arbitrary combinations of local and global visual features, by using a single index realized as an inverted file. The index was implemented on top of the Lucene retrieval engine. This is particularly useful to allow people to efficiently and interactively check the quality of the retrieval result by exploiting combinations of features, by using a single index realized as an inverted file. The index was implemented on top of the Lucene retrieval engine. This is particularly useful to allow people to efficiently and interactively check the quality of the retrieval result by exploiting combinations of various features when using various features when using content based retrieval systems. (literal)
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