ML92 Proceedings of the ninth international workshop on Machine learning
A New Algorithm for Graph Matching with Application to Content-Based Image Retrieval
Proceedings of the Joint IAPR International Workshop on Structural, Syntactic, and Statistical Pattern Recognition
Introduction to combinatorial pyramids
Digital and image geometry
Mining Molecular Fragments: Finding Relevant Substructures of Molecules
ICDM '02 Proceedings of the 2002 IEEE International Conference on Data Mining
gSpan: Graph-Based Substructure Pattern Mining
ICDM '02 Proceedings of the 2002 IEEE International Conference on Data Mining
A quickstart in frequent structure mining can make a difference
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
GREW-A Scalable Frequent Subgraph Discovery Algorithm
ICDM '04 Proceedings of the Fourth IEEE International Conference on Data Mining
Vision pyramids that do not grow too high
Pattern Recognition Letters - Special issue: In memoriam Azriel Rosenfeld
Frequent Substructure-Based Approaches for Classifying Chemical Compounds
IEEE Transactions on Knowledge and Data Engineering
Combining Regions and Patches for Object Class Localization
CVPRW '06 Proceedings of the 2006 Conference on Computer Vision and Pattern Recognition Workshop
Contains and inside relationships within combinatorial pyramids
Pattern Recognition
GDClust: A Graph-Based Document Clustering Technique
ICDMW '07 Proceedings of the Seventh IEEE International Conference on Data Mining Workshops
RAM: Randomized Approximate Graph Mining
SSDBM '08 Proceedings of the 20th international conference on Scientific and Statistical Database Management
gApprox: Mining Frequent Approximate Patterns from a Massive Network
ICDM '07 Proceedings of the 2007 Seventh IEEE International Conference on Data Mining
Object Recognition by Integrating Multiple Image Segmentations
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part III
IAM Graph Database Repository for Graph Based Pattern Recognition and Machine Learning
SSPR & SPR '08 Proceedings of the 2008 Joint IAPR International Workshop on Structural, Syntactic, and Statistical Pattern Recognition
Graph Classification Based on Dissimilarity Space Embedding
SSPR & SPR '08 Proceedings of the 2008 Joint IAPR International Workshop on Structural, Syntactic, and Statistical Pattern Recognition
Graph embedding with constraints
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
Text classification using graph mining-based feature extraction
Knowledge-Based Systems
Corpus callosum MR image classification
Knowledge-Based Systems
Context based object categorization: A critical survey
Computer Vision and Image Understanding
Efficient algorithms for node disjoint subgraph homeomorphism determination
DASFAA'08 Proceedings of the 13th international conference on Database systems for advanced applications
Full duplicate candidate pruning for frequent connected subgraph mining
Integrated Computer-Aided Engineering
Mining Frequent Subgraph Patterns from Uncertain Graph Data
IEEE Transactions on Knowledge and Data Engineering
Approximate weighted frequent pattern mining with/without noisy environments
Knowledge-Based Systems
Image Classification Using Subgraph Histogram Representation
ICPR '10 Proceedings of the 2010 20th International Conference on Pattern Recognition
Assessing the role of spatial relations for the object recognition task
CIARP'10 Proceedings of the 15th Iberoamerican congress conference on Progress in pattern recognition, image analysis, computer vision, and applications
Efficient discovery of frequent subgraph patterns in uncertain graph databases
Proceedings of the 14th International Conference on Extending Database Technology
An efficient graph-mining method for complicated and noisy data with real-world applications
Knowledge and Information Systems - Special Issue on "Context-Aware Data Mining (CADM)"
Frequent approximate subgraphs as features for graph-based image classification
Knowledge-Based Systems
Feature selection for graph-based image classifiers
IbPRIA'05 Proceedings of the Second Iberian conference on Pattern Recognition and Image Analysis - Volume Part II
A graph-matching kernel for object categorization
ICCV '11 Proceedings of the 2011 International Conference on Computer Vision
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Graph-based data representations are an important research topic due to the suitability of this kind of data structure to model entities and the complex relations among them. In computer vision, graphs have been used to model images in order to add some high level information (relations) to the low-level representation of individual parts. How to deal with these representations for specific tasks is not easy due to the complexity of the data structure itself. In this paper we propose to use a graph mining technique for image classification, introducing approximate patterns discovery in the mining process in order to allow certain distortions in the data being modeled. We are proposing to combine a powerful graph-based image representation adapted to this specific task and frequent approximate subgraph (FAS) mining algorithms in order to classify images. In the case of image representation we are proposing to use more robust descriptors than our previous approach in this topic, and we also suggest a criterion to select the isomorphism threshold for the graph mining step. This proposal is tested in two well-known collections to show the improvement with respect to the previous related works.