Pattern recognition and string matching /
This volume is the most comprehensive one in its field. It is a collection of 28 state-of-the-art articles contributed by experts of pattern recognition, string matching, or both. It contains fundamental concepts and notations, as well as reports on current research with respect to both methodology...
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| Other Authors: | , |
| Format: | eBook |
| Language: | English |
| Published: |
Dordrecht ; Boston :
Kluwer Academic Publishers,
2002.
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| Series: | Combinatorial optimization ;
v. 13. |
| Subjects: | |
| Online Access: | Connect to the full text of this electronic book |
Table of Contents:
- Correcting the training data
- Context free grammars and semantic networks for flexible assembly recognition
- Stochastic recognition of occluded objects
- Approximate string matching for angular string elements with applications to on-line and off-line handwriting recognition
- Uniform, fast convergence of arbitrarily tight upper and lower bounds on the Bayes error
- Building RBF networks for time series classification by boosting
- Similarity measures and clustering of string patterns
- Pattern recognition for intrusion detection in computer networks
- Model-based pattern recognition
- Structural pattern recognition in graphs
- Deriving pseudo-probabilities of correctness given scores (DPPS)
- Weighed mean and generalized median of strings
- A region-based algorithm for classifier-independent feature selection
- Inference of K-piecewise testable tree languages
- Mining partially periodic patterns with unknown periods from event stream
- Combination of classifiers for supervised learning: A survey
- Image segmentation and pattern recognition: A novel concept, the histogram of connected elements
- Prototype extraction for k-NN classifiers using median strings
- Cyclic string matching: Efficient extract and approximate algorithms
- Homogeneity, autocorrelation and anisotropy in patterns
- Robust structural indexing through quasi-invariant shape signatures and feature generation
- Energy minimisation methods for static and dynamic curve matching
- Recent feature selection methods in statistical pattern recognition
- Fast image segmentation under noise
- Set analysis of coincident errors and its applications for combining classifiers
- Enhanced neighbourhood specifications for pattern classification
- Algorithmic synthesis in neural network training for pattern recognition
- Binary strings and multi-class learning problems.