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Hybrid methods in pattern recognition /
The field of pattern recognition has seen enormous progress since its beginnings almost 50 years ago. A large number of different approaches have been proposed. Hybrid methods aim at combining the advantages of different paradigms within a single system. Hybrid Methods in Pattern Recognition is a co...
| Clasificación: | Libro Electrónico |
|---|---|
| Otros Autores: | , |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
River Edge, N.J. :
World Scientific,
©2002.
|
| Colección: | Series in machine perception and artificial intelligence ;
v. 47. |
| Temas: | |
| Acceso en línea: | Texto completo |
MARC
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| 245 | 0 | 0 | |a Hybrid methods in pattern recognition / |c editors, H. Bunke, A. Kandel. |
| 260 | |a River Edge, N.J. : |b World Scientific, |c ©2002. | ||
| 300 | |a 1 online resource (xii, 324 pages) : |b illustrations | ||
| 336 | |a text |b txt |2 rdacontent | ||
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| 490 | 1 | |a Series in machine perception and artificial intelligence ; |v v. 47 | |
| 504 | |a Includes bibliographical references. | ||
| 588 | 0 | |a Print version record. | |
| 505 | 0 | |a Preface; Contents; Neuro-Fuzzy Systems; Chapter 1 Fuzzification of Neural Networks for Classification Problems; Neural Networks for Structural Pattern Recognition; Chapter 2 Adaptive Graphic Pattern Recognition: Foundations and Perspectives; Chapter 3 Adaptive Self-Organizing Map in the Graph Domain; Clustering for Hybrid Systems; Chapter 4 From Numbers to Information Granules: A Study in Unsupervised Learning and Feature Analysis; Combining Neural Networks and Hidden Markov Models; Chapter 5 Combination of Hidden Markov Models and Neural Networks for Hybrid Statistical Pattern Recognition. | |
| 505 | 8 | |a Chapter 6 From Character to Sentences: A Hybrid Neuro-Markovian System for On-Line Handwriting RecognitionMultiple Classifier Systems; Chapter 7 Multiple Classifier Combination: Lessons and Next Steps; Chapter 8 Design of Multiple Classifier Systems; Chapter 9 Fusing Neural Networks Through Fuzzy Integration; Applications of Hybrid Systems; Chapter 10 Hybrid Data Mining Methods in Image Processing; Chapter 11 Robust Fingerprint Identification Based on Hybrid Pattern Recognition Methods; Chapter 12 Text Categorization Using Learned Document Features. | |
| 520 | |a The field of pattern recognition has seen enormous progress since its beginnings almost 50 years ago. A large number of different approaches have been proposed. Hybrid methods aim at combining the advantages of different paradigms within a single system. Hybrid Methods in Pattern Recognition is a collection of articles describing recent progress in this emerging field. It covers topics such as the combination of neural nets with fuzzy systems or hidden Markov models, neural networks for the processing of symbolic data structures, hybrid methods in data mining, the combination of symbolic and s. | ||
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| 650 | 0 | |a Pattern recognition systems. | |
| 650 | 0 | |a Neural networks (Computer science) | |
| 650 | 2 | |a Pattern Recognition, Automated | |
| 650 | 2 | |a Neural Networks, Computer | |
| 650 | 6 | |a Reconnaissance des formes (Informatique) | |
| 650 | 6 | |a Réseaux neuronaux (Informatique) | |
| 650 | 7 | |a COMPUTERS |x Optical Data Processing. |2 bisacsh | |
| 650 | 7 | |a Neural networks (Computer science) |2 fast | |
| 650 | 7 | |a Pattern recognition systems |2 fast | |
| 700 | 1 | |a Bunke, Horst, |d 1949- |1 https://id.oclc.org/worldcat/entity/E39PCjtrWx4cfxRY4xpKqhfxwC | |
| 700 | 1 | |a Kandel, Abraham. | |
| 758 | |i has work: |a Hybrid methods in pattern recognition (Text) |1 https://id.oclc.org/worldcat/entity/E39PCGxWQBCMkfQcgbprbkCgfC |4 https://id.oclc.org/worldcat/ontology/hasWork | ||
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| 830 | 0 | |a Series in machine perception and artificial intelligence ; |v v. 47. | |
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