The dissimilarity representation for pattern recognition: foundations and applications
Saved in:
| Main Author: | |
|---|---|
| Format: | Electronic eBook |
| Language: | English |
| Published: |
New Jersey
World Scientific
c2005
|
| Series: | Series in machine perception and artificial intelligence
v. 64 |
| Subjects: | |
| Online Access: | FAW01 FAW02 Volltext |
| Item Description: | Includes bibliographical references and index Preface; Notation and basic terminology; Abbreviations; Contents; 1. Introduction; 1.1 Recognizing the pattern; 1.2 Dissimilarities for representation; 1.3 Learning from examples; 1.4 Motivation of the use of dissimilarity representations; 1.5 Relation to kernels; 1.6 Outline of the book; 1.7 In summary; PART 1 Concepts and theory; 2. Spaces; 3. Characterization of dissimilarities; 4. Learning approaches; 5. Dissimilarity measures; PART 2 Practice; 6. Visualization; 7. Further data exploration; 8. One-class classifiers; 9. Classification; 10. Combining 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 in |
| Physical Description: | 1 Online-Ressource (xxvi, 607 p.) |
| ISBN: | 9789812565303 9789812703170 9812565302 9812703179 |
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MARC
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| 500 | |a 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 in | ||
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| spelling | Pękalska, Elżbieta Verfasser aut The dissimilarity representation for pattern recognition foundations and applications Elżbieta Pękalska, Robert P.W. Duin New Jersey World Scientific c2005 1 Online-Ressource (xxvi, 607 p.) txt rdacontent c rdamedia cr rdacarrier Series in machine perception and artificial intelligence v. 64 Includes bibliographical references and index Preface; Notation and basic terminology; Abbreviations; Contents; 1. Introduction; 1.1 Recognizing the pattern; 1.2 Dissimilarities for representation; 1.3 Learning from examples; 1.4 Motivation of the use of dissimilarity representations; 1.5 Relation to kernels; 1.6 Outline of the book; 1.7 In summary; PART 1 Concepts and theory; 2. Spaces; 3. Characterization of dissimilarities; 4. Learning approaches; 5. Dissimilarity measures; PART 2 Practice; 6. Visualization; 7. Further data exploration; 8. One-class classifiers; 9. Classification; 10. Combining 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 in COMPUTERS / Optical Data Processing bisacsh Pattern perception fast Pattern recognition systems fast Pattern perception Pattern recognition systems Duin, Robert P. W. Sonstige oth http://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&db=nlabk&AN=174590 Aggregator Volltext |
| spellingShingle | Pękalska, Elżbieta The dissimilarity representation for pattern recognition foundations and applications COMPUTERS / Optical Data Processing bisacsh Pattern perception fast Pattern recognition systems fast Pattern perception Pattern recognition systems |
| title | The dissimilarity representation for pattern recognition foundations and applications |
| title_auth | The dissimilarity representation for pattern recognition foundations and applications |
| title_exact_search | The dissimilarity representation for pattern recognition foundations and applications |
| title_full | The dissimilarity representation for pattern recognition foundations and applications Elżbieta Pękalska, Robert P.W. Duin |
| title_fullStr | The dissimilarity representation for pattern recognition foundations and applications Elżbieta Pękalska, Robert P.W. Duin |
| title_full_unstemmed | The dissimilarity representation for pattern recognition foundations and applications Elżbieta Pękalska, Robert P.W. Duin |
| title_short | The dissimilarity representation for pattern recognition |
| title_sort | the dissimilarity representation for pattern recognition foundations and applications |
| title_sub | foundations and applications |
| topic | COMPUTERS / Optical Data Processing bisacsh Pattern perception fast Pattern recognition systems fast Pattern perception Pattern recognition systems |
| topic_facet | COMPUTERS / Optical Data Processing Pattern perception Pattern recognition systems |
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