Structural Pattern Recognition with Graph Edit Distance
Approximation Algorithms and Applications
Part of the Advances in Computer Vision and Pattern Recognition book series (ACVPR)
Part of the Advances in Computer Vision and Pattern Recognition book series (ACVPR)
This unique text/reference presents a thorough introduction to the field of structural pattern recognition, with a particular focus on graph edit distance (GED), one of the most flexible graph distance models available. The book also provides a detailed review of a diverse selection of novel methods related to GED, and concludes by suggesting possible avenues for future research.
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Researchers and graduate students interested in the field of structural pattern recognition will find this focused work to be an essential reference on the latest developments in GED.
Dr. Kaspar Riesen is a university lecturer of computer science in the Institute for Information Systems at the University of Applied Sciences and Arts Northwestern Switzerland, Olten, Switzerland.