Titlebook: Structural, Syntactic, and Statistical Pattern Recognition; Joint IAPR Internati Pasi Fränti,Gavin Brown,Marcello Pelillo Conference procee

McKinley

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书目名称Structural, Syntactic, and Statistical Pattern Recognition网络公开度学科排名




书目名称Structural, Syntactic, and Statistical Pattern Recognition被引频次




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书目名称Structural, Syntactic, and Statistical Pattern Recognition读者反馈学科排名

轻浮女

Improving Approximate Graph Edit Distance Using Genetic Algorithmsint, we implement a search procedure based on a genetic algorithm in order to improve the approximation quality. In an experimental evaluation on three real world data sets a substantial gain of distance accuracy is empirically verified.

敌手

CHECK

Node Centrality for Continuous-Time Quantum Walksly defined quantum states. We investigate how the importance varies as we change the initial state of the walk and the Hamiltonian of the system. We find that, for a suitable combination of the two, the importance of a vertex is almost linearly correlated with its degree. Finally, we evaluate the proposed measure on two commonly used networks.

全等

Max-Correlation Embedding Computation the incidence mapping of the graph. We illustrate the utility of the method for purposes of approximating the colour sensitivity functions of a set of over 20 commercially available digital cameras using a library of spectral reflectance measurements.

不安

预定

A Graph Kernel from the Depth-Based Representations of high dimensional depth-based complexity information. Based on the new representation, we establish a possible correspondence between vertices of two graphs that allows us to construct a matching-based graph kernel. Experiments on graphs from computer vision datasets demonstrate the effectiveness of our kernel.

长处

Conquest

Myelin