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  • Structural, Syntactic, and Statistical Pattern Recognition: Joint IAPR International Workshop, S+SSPR 2014, Joensuu, Finland, August 20-22, 2014, Proceedings

    Structural, Syntactic, and Statistical Pattern Recognition by Fränti, Pasi; Brown, Gavin; Loog, Marco;

    Joint IAPR International Workshop, S+SSPR 2014, Joensuu, Finland, August 20-22, 2014, Proceedings

    Series: Lecture Notes in Computer Science; 8621;

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    Long description:

    This book constitutes the proceedings of the Joint IAPR International Workshop on Structural, Syntactic, and Statistical Pattern Recognition, S+SSPR 2014; comprising the International Workshop on Structural and Syntactic Pattern Recognition, SSPR, and the International Workshop on Statistical Techniques in Pattern Recognition, SPR. The total of 25 full papers and 22 poster papers included in this book were carefully reviewed and selected from 78 submissions. They are organized in topical sections named: graph kernels; clustering; graph edit distance; graph models and embedding; discriminant analysis; combining and selecting; joint session; metrics and dissimilarities; applications; partial supervision; and poster session.

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    Table of Contents:

    Graph Kernels.- A Graph Kernel from the Depth-Based Representation.- Incorporating Molecule’s Stereoisomerism within the Machine Learning Framework.- Transitive State Alignment for the Quantum Jensen-Shannon Kernel.- Clustering.- Balanced K-Means for Clustering.- Poisoning Complete-Linkage Hierarchical Clustering.- A Comparison of Categorical Attribute Data Clustering Methods.- Graph Edit Distance.- Improving Approximate Graph Edit Distance Using Genetic Algorithms.- Approximate Graph Edit Distance Guided by Bipartite Matching of Bags of Walks.- A Hausdorff Heuristic for Efficient Computation of Graph Edit Distance.- Graph Models and Embedding.- Flip-Flop Sublinear Models for Graphs.- Node Centrality for Continuous-Time Quantum Walks.- Max-Correlation Embedding Computation.- Discriminant Analysis.- Fast Gradient Computation for Learning with Tensor Product Kernels and Sparse Training Labels.- Nonlinear Discriminant Analysis Based on Probability Estimation by Gaussian Mixture Model.- Combining and Selecting.- Information Theoretic Feature Selection in Multi-label Data through Composite Likelihood.- Majority Vote of Diverse Classifiers for Late Fusion.- Entropic Graph Embedding via Multivariate Degree Distributions.- On Parallel Lines in Noisy Forms.- Metrics and Dissimilarities.- Metric Learning in Dissimilarity Space for Improved Nearest Neighbor Performance.- Matching Similarity for Keyword-Based Clustering.- Applications.- Quantum vs Classical Ranking in Segment Grouping.- Remove Noise in Video with 3D Topological Maps.- Video Analysis of a Snooker Footage Based on a Kinematic Model.- Partial Supervision.- Evaluating Classification Performance with only Positive and Unlabeled Samples.- Who Is Missing? A New Pattern Recognition Puzzle.- Poster Session.- Edit Distance Computed by Fast Bipartite Graph Matching.- Statistical Method for Semantic Segmentation of Dominant Plane from Remote Exploration Image Sequence.- Analyses on Generalization Error of Ensemble Kernel Regressors.- Structural Human Shape Analysis for Modeling and Recognition.- On Cross-Validation for MLP Model Evaluation.- Weighted Mean Assignment of a Pair of Correspondences Using Optimisation Functions.- Chemical Symbol Feature Set for Handwritten Chemical Symbol Recognition.- About Combining Metric Learning and Prototype Generation.- Tracking System with Re-identification Using a RGB String Kernel.- Towards Scalable Prototype Selection by Genetic Algorithms with Fast Criteria.- IOWA Operators and Its Application to Image Retrieval.- On Optimum Thresholding of Multivariate Change Detectors.- Commute Time for a Gaussian Wave Packet on a Graph.- Properties of Object-Level Cross-Validation Schemes for Symmetric Pair-Input Data.- A Binary Factor Graph Model for Biclustering.- Improved BLSTM Neural Networks for Recognition of On-Line Bangla Complex Words.- A Ranking Part Model for Object Detection.- Regular Decomposition of Multivariate Time Series and Other Matrices.- Texture Synthesis:From Convolutional RBMs to Efficient Deterministic Algorithms.- Improved Object Matching Using Structural Relations.- Designing LDPC Codes for ECOC Classification Systems.- Unifying Probabilistic Linear Discriminant Analysis Variants in Biometric Authentication.

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