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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.
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| Colección: | Series in machine perception and artificial intelligence ;
v. 47. |
| Temas: | |
| Acceso en línea: | Texto completo |
Tabla de Contenidos:
- 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.
- 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.