SHREC10 Track: Protein Model Classification

L. Mavridis, V. Venkatraman, D. Ritchie, N. Morikawa, R. Andonov, A. Cornu, N. Malod-Dognin, J. Nicolas, Maja Temerinac-Ott, M. Reisert, Hans Burkhardt, A. Axenopoulos, P. Daras
Eurographics Workshop on 3D Object Retrieval, Eurographics Association: 117--124, 2010
Abstract: This paper presents the results of the 3D Shape Retrieval Contest 2010 (SHREC10) 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.
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  author       = "L. Mavridis and V. Venkatraman and D. Ritchie and N. Morikawa and R. Andonov and A. Cornu and N. Malod-Dognin and J. Nicolas and M. Temerinac-Ott and M. Reisert and H. Burkhardt and A. Axenopoulos and P. Daras",
  title        = "SHREC10 Track: Protein Model Classification",
  booktitle    = "Eurographics Workshop on 3D Object Retrieval",
  pages        = "117--124",
  year         = "2010",
  publisher    = "Eurographics Association",
  organization = "Eurographics",
  keywords     = "Curve, surface, solid, and object representations, Geometric algorithms",
  url          = "http://lmb.informatik.uni-freiburg.de/Publications/2010/TB10"

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