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dc.contributor.authorMavridis, L.en_US
dc.contributor.authorVenkatraman, V.en_US
dc.contributor.authorRitchie, D. W.en_US
dc.contributor.authorMorikawa, N.en_US
dc.contributor.authorAndonov, R.en_US
dc.contributor.authorCornu, A.en_US
dc.contributor.authorMalod-Dognin, N.en_US
dc.contributor.authorNicolas, J.en_US
dc.contributor.authorTemerinac-Ott, M.en_US
dc.contributor.authorReisert, M.en_US
dc.contributor.authorBurkhardt, H.en_US
dc.contributor.authorAxenopoulos, A.en_US
dc.contributor.authorDaras, P.en_US
dc.contributor.editorMohamed Daoudi and Tobias Schrecken_US
dc.date.accessioned2013-10-21T16:10:04Z
dc.date.available2013-10-21T16:10:04Z
dc.date.issued2010en_US
dc.identifier.isbn978-3-905674-22-4en_US
dc.identifier.issn1997-0471en_US
dc.identifier.urihttp://dx.doi.org/10.2312/3DOR/3DOR10/117-124en_US
dc.description.abstractThis paper presents the results of the 3D Shape Retrieval Contest 2010 (SHREC'10) track Protein Models Classification. The aim of this track is to evaluate how well 3D shape recognition algorithms can classify protein structures according to the CATH [CSL?08] superfamily classification. Five groups participated in this track, using a total of six methods, and for each method a set of ranked predictions was submitted for each classification task. The evaluation of each method is based on the nearest neighbour and area under the curve(AUC) metrics.en_US
dc.publisherThe Eurographics Associationen_US
dc.titleSHREC'10 Track: Protein Model Classificationen_US
dc.description.seriesinformationEurographics Workshop on 3D Object Retrievalen_US


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