Dissimilarity Representation for Pattern Recognition Foundations And Applications

This book provides a fundamentally new approach to pattern recognition in which objects are characterized by relations to other objects instead of by using features or models. This 'dissimilarity representation' bridges the gap between the traditionally opposing approaches of statistical and structural pattern recognition. Physical phenomena, objects and events in the world are related in various and often complex ways. Such relations are usually modeled in the form of graphs or diagrams. While this is useful for communication between experts, such representation is difficult to combine and integrate by machine learning procedures. However, if the relations are captured by sets of dissimilarities, general data analysis procedures may be applied for analysis.Pekalska, Elzbieta is the author of 'Dissimilarity Representation for Pattern Recognition Foundations And Applications', published 2006 under ISBN 9789812565303 and ISBN 9812565302.