Image clustering through community detection on hybrid image similarity graphs

Papadopoulos, S; Zigkolis, C; Tolias, G; Kalantidis, Y; Mylonas, P; Kompatsiaris, Y; Vakali, A

dc.contributor.author	Papadopoulos, S	en
dc.contributor.author	Zigkolis, C	en
dc.contributor.author	Tolias, G	en
dc.contributor.author	Kalantidis, Y	en
dc.contributor.author	Mylonas, P	en
dc.contributor.author	Kompatsiaris, Y	en
dc.contributor.author	Vakali, A	en
dc.date.accessioned	2014-03-01T02:52:31Z
dc.date.available	2014-03-01T02:52:31Z
dc.date.issued	2010	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/35897
dc.subject	Community Detection	en
dc.subject	Content Based Image Retrieval	en
dc.subject	Image Clustering	en
dc.subject	Image Similarity	en
dc.subject	Indexing Terms	en
dc.subject	Information Overload	en
dc.subject	Photo Sharing	en
dc.subject	User Generated Content	en
dc.title	Image clustering through community detection on hybrid image similarity graphs	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1109/ICIP.2010.5653478	en
heal.identifier.secondary	http://dx.doi.org/10.1109/ICIP.2010.5653478	en
heal.publicationDate	2010	en
heal.abstract	The wide adoption of photo sharing applications such as Flickr© and the massive amounts of user-generated content uploaded to them raises an information overload issue for users. An established technique to overcome such an overload is to cluster images into groups based on their similarity and then use the derived clusters to assist navigation and browsing of the collection. In	en
heal.journalName	Image Processing, IEEE International Conference	en
dc.identifier.doi	10.1109/ICIP.2010.5653478	en