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Graph matching and learning in pattern recognition in the last 10 years
In this paper, we examine the main advances registered in the last ten years in Pattern
Recognition methodologies based on graph matching and related techniques, analyzing …
Recognition methodologies based on graph matching and related techniques, analyzing …
Graph neural networks using local descriptions in attributed graphs: an application to symbol recognition and hand written character recognition
Graph-based methods have been widely used by the document image analysis and
recognition community, as the different objects and the content in document images is best …
recognition community, as the different objects and the content in document images is best …
Hierarchical graph embedding in vector space by graph pyramid
Loss of information is the major challenge in graph embedding in vector space which
reduces the impact of representational power of graphs in pattern recognition tasks. The …
reduces the impact of representational power of graphs in pattern recognition tasks. The …
Stochastic graphlet embedding
Graph-based methods are known to be successful in many machine learning and pattern
classification tasks. These methods consider semistructured data as graphs where nodes …
classification tasks. These methods consider semistructured data as graphs where nodes …
A histogram-based approach to calculate graph similarity using graph neural networks
Deep learning has revolutionized the field of pattern recognition and machine learning by
exhibiting exceptional efficiency in recognizing patterns. The success of deep learning can …
exhibiting exceptional efficiency in recognizing patterns. The success of deep learning can …
Deep adaptive graph clustering via von Mises-Fisher distributions
Graph clustering has been a hot research topic and is widely used in many fields, such as
community detection in social networks. Lots of works combining auto-encoder and graph …
community detection in social networks. Lots of works combining auto-encoder and graph …
Reducing human effort in engineering drawing validation
Oil & Gas facilities are extremely huge and have complex industrial structures that are
documented using thousands of printed sheets. During the last years, it has been a …
documented using thousands of printed sheets. During the last years, it has been a …
[کتاب][B] Graph-based social media analysis
I Pitas - 2016 - books.google.com
This book provides a comprehensive introduction to the use of graph analysis in the study of
social media and digital media. It covers the following topics: graphs in social media, graph …
social media and digital media. It covers the following topics: graphs in social media, graph …
A novel multi-view clustering approach via proximity-based factorization targeting structural maintenance and sparsity challenges for text and image categorization
Multi-view data contains a set of features representing different perspectives associated with
the same data and this phenomenon can be commonly observed in real-world applications …
the same data and this phenomenon can be commonly observed in real-world applications …
Diffusion network embedding
In network embedding, random walks play a fundamental role in preserving network
structures. However, random walk methods have two limitations. First, they are unstable …
structures. However, random walk methods have two limitations. First, they are unstable …