Title Pattern recognition applications and methods : International Conference, ICPRAM 2013, Barcelona, Spain, February 15-18, 2013, Revised selected papers / Ana Fred, Maria De Marsico, editors

Published Cham : Springer, 2015 ©2015

Click on the following:
Springer eBooks
Springer Engineering eBooks

Copies

Description 1 online resource (xv, 312 pages) : illustrations (some color) Series Advances in Intelligent Systems and Computing, 2194-5357 ; volume 318 Advances in intelligent systems and computing ; volume 318. Contents Preface; Organization; Contents; Part I Theory and Methods; A Two-Part Approach to Face Recognition: Generalized Hough Transform and Image Descriptors; 1 Introduction; 2 Method; 2.1 Modified GHT; 2.2 Gradient Distance Descriptor; 3 Results and Discussion; 4 Conclusions; References; Improved Boosting Performance by Explicit Handling of Ambiguous Positive Examples; 1 Introduction; 1.1 Relation to Bootstrapping Methods; 1.2 Contributions; 2 Relation to Previous Work; 3 Boosting Theory; 3.1 Convex-Loss Boosting Algorithms; 3.2 Robust Boosting Algorithms; 4 A Two-Pass Exclusion Extension 4.1 Inverted Cascade5 Experiments; 6 Results; 6.1 Comparison of Boosting Algorithms; 6.2 Bootstrapping Methods in Relation to Outlier Exclusion; 7 Discussion and Future Work; 8 Conclusions; References; Discriminative Dimensionality Reduction for the Visualization of Classifiers; 1 Introduction; 2 Supervised Visualization Based on the Fisher Information; 2.1 Computation of the Class Probabilities; 2.2 Approximation of Minimum Path Integrals; 3 Training a Discriminative Visualization Mapping; 4 Visualization of Classifiers; 5 Conclusions; References Online Unsupervised Neural-Gas Learning Method for Infinite Data Streams1 Introduction; 2 Related Work; 3 Proposed Algorithm (AING); 3.1 General Behaviour; 3.2 AING Distance Threshold; 3.3 AING Merging Process; 4 Experimental Evaluation; 4.1 Experiments on Synthetic Data; 4.2 Experiments on Real Datasets; 5 Conclusions and Future Work; References; The Path Kernel: A Novel Kernel for Sequential Data; 1 Introduction; 2 Kernels and Sequences; 2.1 Sequence Similarity Measures; 3 The Path Kernel; 3.1 Efficient Computation; 3.2 Ground Kernel Choice; 4 Experiments; 5 Conclusions; References A MAP Approach to Evidence Accumulation Clustering1 Introduction; 2 Probabilistic Model; 3 Optimization Algorithm; 3.1 Computation of a Search Direction; 3.2 Computation of an Optimal Step Size; 3.3 Complexity; 4 Related Work; 5 Experiments and Results; 5.1 UCI and Synthetic Data; 5.2 Text Data; 6 Conclusions; References; Feature Discretization with Relevance and Mutual Information Criteria; 1 Introduction; 1.1 Our Contribution; 2 Background; 2.1 Entropy and Mutual Information; 2.2 Feature Discretization; 2.3 Unsupervised Discretization; 2.4 Supervised Discretization; 3 Proposed Methods 3.1 Relevance-Based LBG3.2 Mutual Information Discretization; 4 Experimental Evaluation; 4.1 Comparison Between Our Approaches; 4.2 Comparison with Existing Methods; 5 Conclusions; References; Multiclass Semi-supervised Learning on Graphs Using Ginzburg-Landau Functional Minimization; 1 Introduction; 2 Data Segmentation with the Ginzburg-Landau Model; 2.1 Application of Diffuse Interface Models to Graphs; 3 Multiclass Extension; 3.1 Generalized Difference Function; 3.2 Computational Algorithm; 4 Results; 4.1 Synthetic Data; 4.2 Image Segmentation; 4.3 Benchmark Sets; 5 Conclusions Summary This book contains the extended and revised versions of a set of selected papers from the 2nd International Conference on Pattern Recognition (ICPRAM 2013), held in Barcelona, Spain, from 15 to 18 February, 2013. ICPRAM was organized by the Institute for Systems and Technologies of Information, Control and Communication (INSTICC) and was held in cooperation with the Association for the Advancement of Artificial Intelligence (AAAI). The hallmark of this conference was to encourage theory and practice to meet in a single venue. The focus of the book is on contributions describing applications of Pattern Recognition techniques to real-world problems, interdisciplinary research, experimental and/or theoretical studies yielding new insights that advance Pattern Recognition methods Analysis patroonherkenning pattern recognition machine vision engineering computational science beeldverwerking image processing spraak speech kunstmatige intelligentie artificial intelligence Engineering (General) Techniek (algemeen) Notes Includes author index Bibliography References Notes English Online resource; title from PDF title page (SpringerLink, viewed January 16, 2015) Subject Pattern perception -- Congresses Pattern recognition systems -- Congresses Artificial intelligence. Computer vision. Imaging systems & technology. COMPUTERS -- General. Pattern perception Pattern recognition systems Genre/Form Electronic books proceedings (reports) Conference papers and proceedings Conference papers and proceedings. Actes de congrès. Form Electronic book Author Fred, Ana, editor. De Marsico, Maria, editor. ISBN 9783319126104 3319126105

Other Titles ICPRAM 2013

  Permalink