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...
| Други автори: | Bunke, Horst., Kandel, Abraham. |
|---|---|
| Формат: | Електронна книга |
| Език: | English |
| Публикувано: |
River Edge, N.J. :
World Scientific,
℗♭2002.
|
| Серия: |
Series in machine perception and artificial intelligence ;
v. 47. |
| Предмети: | |
| Онлайн достъп: |
http://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=210636 |
| Подобни документи: |
Print version::
Hybrid methods in pattern recognition. |
Съдържание:
- 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.