Frequent approximate subgraphs as features for graph-based image classification

Author:

Acosta-Mendoza Niusvel,Gago-Alonso Andrés,Medina-Pagola José E.

Publisher

Elsevier BV

Subject

Artificial Intelligence,Information Systems and Management,Management Information Systems,Software

Reference38 articles.

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2. Image classification using subgraph histogram representation;Bahadir,2010

3. C. Borgelt, Canonical forms for frequent graph mining, in: Proceedings of the 30th Annual Conference of the Gesellschaft für Klassifikation e.V., Universitat Berlin, 2006, pp. 8–10.

4. C. Borgelt, M. Berthold, Mining molecular fragments: finding relevant substructures of molecules, in: Proceedings of 2002 International Conference on Data Mining (ICDM’02), Maebashi, Japan, 2002, pp. 211–218.

5. gapprox: Mining frequent approximate patterns from a massive network;Chen,2007

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