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 …

Benefit from avoiding the utilization of labeled samples, which are usually insufficient in the
real world, unsupervised learning has been regarded as a speedy and powerful strategy on …

These days, clustering is one of the most classical themes to analyze data structures in
machine learning and pattern recognition. Recently, the anchor-based graph has been …

High-order graph matching utilizes the high-order relations to establish the
correspondences between two sets of features. It has been formulated as an optimization …

Many tasks in computer vision and pattern recognition are formulated as graph matching
problems. Despite the NP-hard nature of such problems, fast and accurate approximations …

Privacy preservation is a primary concern in social networks which employ a variety of
privacy preservations mechanisms to preserve and protect sensitive user information …

In this paper, we propose a density-based clusters' representatives selection algorithm that
identifies the most central patterns from the dense regions in the dataset. The method, which …

Graph matching is a fundamental NP-problem in computer vision and pattern recognition. In
this paper, we propose a robust approximate graph matching method. The match between …

Representing patterns as labeled graphs is becoming increasingly common in the broad
field of computational intelligence. Accordingly, a wide repertoire of pattern recognition tools …

In this paper we decouple the problem of measuring graph similarity into two sequential
steps. The first step is the linearization of the quadratic assignment problem (QAP) in a low …