Progress in Pattern Recognition

Pattern Matching and Classification.- Estimation in Feedback Loops by Stochastic Learning.- Combining Exhaustive and Approximate Methods for Improved Sub-Graph Matching.- Information Fusion Techniques for Reliably Training Intrusion Detection Systems.- Use of Artificial Neural Networks and Effects of Amino Acid Encodings in the Membrane Protein Prediction Problem.- Computationally Efficient Graph Matching via Energy Vector Extraction.- A Validity Index Based on Cluster Symmetry.- of New Expert and Old Expert Retirement in Ensemble Learning under Drifting Concept.- Comparison of Three Feature Extraction Techniques to Distinguish Between Different Infrasound Signals.- Developing Trading Strategies based on Risk-analysis of Stocks.- Biometrics.- Facial Image Processing with Convolutional Neural Networks.- Time-dependent Interactive Graphical Models for Human Activity Analysis.- A New Lexicon-based Method for Automated Detection of Terrorist Web Documents.- A Neural Network Approach for Multifont and Size-Independent Recognition of Ethiopic Characters.- Automated Classification of Affective States using Facial Thermal Features.- On-line One Stroke Character Recognition Using Directional Features.- Comparison of SVMs in Number Plate Recognition.- Three Different Models for Named Entity Recognition in Bengali.- Comparison of Local and Global Thresholding for Binarization of Cheque Images.- Reading out 2D Barcode PDF417.- Off-Line Hand-Written Farsi/Arabic Word Segmentation into Subword under Overlapped or Connected Conditions.- Iris Biometrics Algorithm for Low Cost Devices.- Optimization on PCA Based Face Recognition Models.- Discriminating Unknown Faces using Eigen-face Approach and a Novelty Filter.- Using Timing to Detect Horror Shots in Horror Movies.- Indoor/Outdoor Scene Classification using Audio and Video Features.

Professor Sameer Singh is Director of the Research School of Informatics, Loughborough University, UK, and serves as Editor-in-Chief of the Springer journal, Pattern Analysis and Applications

From the reviews:"The book is divided into two parts. ... Although in my opinion many articles could have presented more proper conclusions or deeper proofs and evidences, and some of them focused on the practicability of machine learning and pattern recognition from a theoretically point of view, the scientific relevance of the content of the book is good. The authors presented their work at the International Workshop on Advances in Pattern Recognition 2007. Accordingly, the target audience is also academic." (Eleazar Jimenez Serrano, IAPR Newsletter, Vol. 32 (4), October, 2010)