This paper proposes a procedure to train scene text recognition model using robust learned surrogate of edit distance. The proposed method borrows from self-paced learning and filters out the training examples that are hard for surrogate. filtering is performed by judging quality approximation, ramp function, enabling end-to-end training. Following literature, experiments conducted in post-tuni...

Edit distance is a measurement of similarity between two sequences such as strings, point sequences, or polygonal curves. Many matching problems from variety areas, signal analysis, bioinformatics, etc., need to be solved in geometric space. Therefore, the edit (GED) has been studied. In this paper, we describe first strictly sublinear approximate near-linear time algorithm for computing GED co...

In this paper we propose a quadratic programming approach to computing the edit distance of graphs. Whereas the standard edit distance is defined with respect to a minimum-cost edit path between graphs, we introduce the notion of fuzzy edit paths between graphs and provide a quadratic programming formulation for the minimization of fuzzy edit costs. Experiments on real-world graph data demonstr...

Tree edit distance is a conventional dissimilarity measure between labeled trees. However, tree edit distance including unit-cost edit distance contains the similarity of label and that of tree structure simultaneously. Therefore, even if the label similarity between two trees that share many nodes with the same label is high, the high label similarity is hard to be recognized from their tree e...

Generalized maps are widely used to model the topology of nD objects (such as 2D or 3D images) by means of incidence and adjacency relationships between cells (0D vertices, 1D edges, 2D faces, 3D volumes, ...). We have introduced in [1] a map edit distance. This distance compares maps by means of a minimum cost sequence of edit operations that should be performed to transform a map into another...

typographical data entry errors and incomplete documents, produce imperfect records in real world databases. these errors generate distinct records which belong to the same entity. the aim of approximate record matching is to find multiple records which belong to an entity. in this paper, an algorithm for approximate record matching is proposed that can be adapted automatically with input error...