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Pattern Recognition and Data Mining als Buch

Pattern Recognition and Data Mining

Third International Conference on Advances in Pattern Recognition, ICAR 2005, Bath, UK, August 22-25, 2005, Part…
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This LNCS volume contains the papers presented at the 3rd International C- ferenceonAdvances in PatternRecognition(ICAPR2005)organizedin August, 2005 in the beautiful city of Bath, UK. The conference was ?rst organized in November 1998 in Plymouth, U... weiterlesen


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Pattern Recognition and Data Mining als Buch
Titel: Pattern Recognition and Data Mining

ISBN: 3540287574
EAN: 9783540287575
Third International Conference on Advances in Pattern Recognition, ICAR 2005, Bath, UK, August 22-25, 2005, Part I.
'Lecture Notes in Computer Science'. 'Image Processing, Computer Vision, Pattern Recognition, and Graphics'.
2005. Auflage.
Sprache: Englisch.
Herausgegeben von Chid Apte, Petra Perner, Maneesha Singh
Springer Berlin Heidelberg

18. August 2005 - kartoniert - 720 Seiten


This LNCS volume contains the papers presented at the 3rd International C- ferenceonAdvances in PatternRecognition(ICAPR2005)organizedin August, 2005 in the beautiful city of Bath, UK. The conference was ?rst organized in November 1998 in Plymouth, UK and subsequently in March 2001 in Rio de Janeiro, Brazil. The conference encouraged papers that made signi?cant th- reticalandapplication-basedcontributions inpatternrecognition. The emphasis was on an open exchange of ideas and shared learning. The papers submitted to ICAPR 2005 were thoroughly reviewed by up to three referees per paper and less than 40% of the submitted papers were accepted. The papers have been ?nally published as two volumes of LNCS and these are organized under the themes of Pattern Recognition and Data Mining (which included papers from the trackson PatternRecognition Methods, Knowledgeand Learning,and Data Mining), and Pattern Recognition and Image Analysis (which included papers from the Applications track). From the conference technical programme point of view, the ?rst volume contains papers on pattern recognition, data mining, signal processing and OCR/document analysis. The second volume contains - pers from the Workshop on Pattern Recognition for Crime Prevention, Security and Surveillance, Biometrics, Image Processing and Medical Imaging. ICAPR 2005was run in parallel with the InternationalWorkshop on Pattern Recognition for Crime Prevention, Security and Surveillance that was organized onthe22ndofAugust,2005. Thisworkshopbroughttogethera number ofexc- lent papers that focussed on how pattern recognition techniques can be used to developsystemsthathelpwithcrimepreventionanddetection. Onthesameday, a number of tutorials were also organized.


Pattern Recognition and Data Mining.- Enhancing Trie-Based Syntactic Pattern Recognition Using AI Heuristic Search Strategies.- Mathematical Features for Recognizing Preference in Sub-saharan African Traditional Rhythm Timelines.- Empirical Bounds on Error Differences When Using Naive Bayes.- Effective Probability Forecasting for Time Series Data Using Standard Machine Learning Techniques.- A Continuous Weighted Low-Rank Approximation for Collaborative Filtering Problems.- GP Ensemble for Distributed Intrusion Detection Systems.- Clustered Trie Structures for Approximate Search in Hierarchical Objects Collections.- On Adaptive Confidences for Critic-Driven Classifier Combining.- The RW2 Algorithm for Exact Graph Matching.- Making Use of Unelaborated Advice to Improve Reinforcement Learning: A Mobile Robotics Approach.- Consolidated Trees: Classifiers with Stable Explanation. A Model to Achieve the Desired Stability in Explanation.- Discovering Predictive Variables When Evolving Cognitive Models.- Mathematical Morphology and Binary Geodesy for Robot Navigation Planning.- Neural Network Classification: Maximizing Zero-Error Density.- Taxonomy of Classifiers Based on Dissimilarity Features.- Combination of Boosted Classifiers Using Bounded Weights.- Prediction of Commodity Prices in Rapidly Changing Environments.- Develop Multi-hierarchy Classification Model: Rough Set Based Feature Decomposition Method.- On Fitting Finite Dirichlet Mixture Using ECM and MML.- Disease Classification from Capillary Electrophoresis: Mass Spectrometry.- Analyzing Large Image Databases with the Evolving Tree.- A Sequence Labeling Method Using Syntactical and Textual Patterns for Record Linkage.- Recognition Tasks Are Imitation Games.- Use of Input Deformations with Brownian Motion Filters for Discontinuous Regression.- Hierarchical Clustering of Dynamical Systems Based on Eigenvalue Constraints.- An Optimally Weighted Fuzzy k-NN Algorithm.- A Tabu Search Based Method for Minimum Sum of Squares Clustering.- Approximation of Digital Circles by Regular Polygons.- A Novel Feature Fusion Method Based on Partial Least Squares Regression.- Combining Text and Link Analysis for Focused Crawling.- A Weighting Initialization Strategy for Weighted Support Vector Machines.- Configuration of Neural Networks for the Analysis of Seasonal Time Series.- Boosting Feature Selection.- Similarity Searching in Image Retrieval with Statistical Distance Measures and Supervised Learning.- Using Patterns to Generate Prime Numbers.- Empirical Study on Weighted Voting Multiple Classifiers.- Spectral Clustering for Time Series.- A New EM Algorithm for Resource Allocation Network.- A Biased Support Vector Machine Approach to Web Filtering.- A New Approach to Generate Frequent Patterns from Enterprise Databases.- Consolidated Tree Classifier Learning in a Car Insurance Fraud Detection Domain with Class Imbalance.- Missing Data Estimation Using Polynomial Kernels.- Predictive Model for Protein Function Using Modular Neural Approach.- Using kNN Model for Automatic Feature Selection.- Multi-view EM Algorithm for Finite Mixture Models.- Segmentation Evaluation Using a Support Vector Machine.- Detection of Spots in 2-D Electrophoresis Gels by Symmetry Features.- Analysis of MHC-Peptide Binding Using Amino Acid Property-Based Decision Rules.- Accuracy of String Kernels for Protein Sequence Classification.- An Efficient Feature Selection Method for Object Detection.- Multi-SOMs: A New Approach to Self Organised Classification.- Selection of Classifiers Using Information-Theoretic Criteria.- ICA and GA Feature Extraction and Selection for Cloud Classification.- Signal Processing.- A Study on Robustness of Large Vocabulary Mandarin Chinese Continuous Speech Recognition System Based on Wavelet Analysis.- Recognition of Insect Emissions Applying the Discrete Wavelet Transform.- On the Performance of Hurst-Vectors for Speaker Identification Systems.- Transformations of LPC and LSF Parameters to Speech Recognition Features.- Redshift Determination for Quasar Based on Similarity Measure.- Learning with Segment Boundaries for Hierarchical HMMs.- A Bayesian Method for High-Frequency Restoration of Low Sample-Rate Speech.- Probabilistic Tangent Subspace Method for Multiuser Detection.- OCR/Document Analysis.- Feature Extraction for Handwritten Chinese Character by Weighted Dynamic Mesh Based on Nonlinear Normalization.- Post Processing of Handwritten Phonetic Pitman's Shorthand Using a Bayesian Network Built on Geometric Attributes.- Ancient Printed Documents Indexation: A New Approach.- Applying Software Analysis Technology to Lightweight Semantic Markup of Document Text.- Noisy Digit Classification with Multiple Specialist.- Automatic Table Detection in Document Images.- High Performance Classifiers Combination for Handwritten Digit Recognition.- A Novel Approach for Text Detection in Images Using Structural Features.- Optical Flow-Based Segmentation of Containers for Automatic Code Recognition.- Hybrid OCR Combination for Ancient Documents.- New Holistic Handwritten Word Recognition and Its Application to French Legal Amount.- Handwriting Documents Denoising and Indexing Using Hermite Transform.- Evaluation of Commercial OCR: A New Goal Directed Methodology for Video Documents.

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