The use of a graph-based pattern representation induces the need to formulate the main operations required in Pattern Recognition in terms of operations on graphs: classification, usually intended as the comparison between an object and a set of prototypes, and learning, which is the process for obtaining a model of a class starting from a set of known samples, are among the key issues that must be addressed using graph-based techniques. Forty years have passed since the first papers on this topic appear in Pattern Recognition literature: a lot of research effort has been devoted to explore this challenging field and some approaches have been meanwhile consolidated. These notes aren’t a scientific paper but some considerations inspiring my future talk at gbr 2013 conference, a little trip in the word of graphs aimed at better knowing treasures and outstanding locations.
|Titolo:||A One Hour Trip in the World of Graphs, Looking at the Papers of the Last Ten Years|
|Data di pubblicazione:||2013|
|Appare nelle tipologie:||4.1.2 Proceedings con ISBN|