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Statements

Subject Item
n2:RIV%2F00216224%3A14330%2F13%3A00065734%21RIV14-MV0-14330___
rdf:type
n7:Vysledek skos:Concept
dcterms:description
Unprecedented amounts of digital data are becoming available nowadays, but frequently the data lack some semantic information necessary to effectively organize these resources. For images in particular, textual annotations that represent the semantics are highly desirable. Only a small percentage of images is created with reliable annotations, therefore a lot of effort is being invested into automatic image annotation. In this paper, we address the annotation problem from a general perspective and introduce a new annotation model that is applicable to many text assignment problems. We also provide experimental results from several implemented instances of our model. Unprecedented amounts of digital data are becoming available nowadays, but frequently the data lack some semantic information necessary to effectively organize these resources. For images in particular, textual annotations that represent the semantics are highly desirable. Only a small percentage of images is created with reliable annotations, therefore a lot of effort is being invested into automatic image annotation. In this paper, we address the annotation problem from a general perspective and introduce a new annotation model that is applicable to many text assignment problems. We also provide experimental results from several implemented instances of our model.
dcterms:title
Content-based annotation and classification framework: a general multi-purpose approach Content-based annotation and classification framework: a general multi-purpose approach
skos:prefLabel
Content-based annotation and classification framework: a general multi-purpose approach Content-based annotation and classification framework: a general multi-purpose approach
skos:notation
RIV/00216224:14330/13:00065734!RIV14-MV0-14330___
n7:predkladatel
n14:orjk%3A14330
n3:aktivita
n15:P
n3:aktivity
P(GBP103/12/G084), P(VF20102014004)
n3:dodaniDat
n4:2014
n3:domaciTvurceVysledku
n11:1235753 n11:5060699 n11:3165647 n11:8876398
n3:druhVysledku
n8:D
n3:duvernostUdaju
n19:S
n3:entitaPredkladatele
n18:predkladatel
n3:idSjednocenehoVysledku
66867
n3:idVysledku
RIV/00216224:14330/13:00065734
n3:jazykVysledku
n9:eng
n3:klicovaSlova
Automatic image annotation; classication; content-based search; hierarchical approach
n3:klicoveSlovo
n5:Automatic%20image%20annotation n5:content-based%20search n5:hierarchical%20approach n5:classication
n3:kontrolniKodProRIV
[A8FDE156228A]
n3:mistoKonaniAkce
Barcelona, Spain
n3:mistoVydani
New York, NY, USA
n3:nazevZdroje
Proceedings of the 17th International Database Engineering & Applications Symposium
n3:obor
n10:IN
n3:pocetDomacichTvurcuVysledku
4
n3:pocetTvurcuVysledku
4
n3:projekt
n20:VF20102014004 n20:GBP103%2F12%2FG084
n3:rokUplatneniVysledku
n4:2013
n3:tvurceVysledku
Budíková, Petra Zezula, Pavel Botorek, Jan Batko, Michal
n3:typAkce
n17:WRD
n3:zahajeniAkce
2013-01-01+01:00
s:numberOfPages
10
n23:doi
10.1145/2513591.2513651
n13:hasPublisher
ACM
n12:isbn
9781450320252
n22:organizacniJednotka
14330