Mathematical Methodologies in Pattern Recognition and Machine Learning Contributions from the International Conference on Pattern Recognition Applications and Methods, 2012

Mathematical Methodologies in Pattern Recognition and Machine Learning Contributions from the International Conference on Pattern Recognition Applications and Methods, 2012 / edited by Pedro Latorre Carmona, J. Salvador Sánchez, Ana L.N. Fred.

This volume features key contributions from the International Conference on Pattern Recognition Applications and Methods, (ICPRAM 2012,) held in Vilamoura, Algarve, Portugal from February 6th-8th, 2012. The conference provided a major point of collaboration between researchers, engineers and practit...

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Bibliographic Details
Corporate Author: SpringerLink (Online service)
Other Authors: Latorre Carmona, Pedro (Editor), Sánchez, J. Salvador (Editor), Fred, Ana L.N (Editor)
Format: eBook
Language:English
Published: New York, NY : Springer New York : Imprint: Springer, 2013.
Edition:1st ed. 2013.
Series:Springer Proceedings in Mathematics & Statistics, 30
Springer eBook Collection.
Subjects:
System theory.
Mathematical optimization.
Computer science—Mathematics.
Pattern recognition.
Electronic resources (E-books)
Online Access:Click to view e-book
Holy Cross Note:Loaded electronically.
Electronic access restricted to members of the Holy Cross Community.
Table of Contents:
  • On order equivalences between distance and similarity measures on sequences and trees
  • Scalable Corpus Annotation by Graph Construction and Label Propagation
  • Computing the reeb graph for triangle meshes with active contours
  • Efficient Computation of Voronoi Neighbors based on Polytope search in Pattern Recognition
  • Estimation of the common oscillation for Phase Locked Matrix Factorization
  • ASSET: Approximate Stochastic Subgradient Estimation Training for Support Vector Machines
  • Pitch-sensitive Components emerge from Hierarchical Sparse Coding of Natural Sounds
  • Generative Embeddings based on Rican Mixtures: Application to KernelBased Discriminative Classification of Magnetic Resonance Images.-Single-Frame Signal Recovery Using a Similarity-Prior Based on Pearson Type VII MRF
  • Tracking solutions of time varying linear inverse problems
  • Stacked Conditional Random Fields Exploiting Structural Consistencies
  • Segmentation of Vessel Geometries from Medical Images using GPF Deformable Model
  • Robust Deformable Model for Segmenting the Left Ventricle in 3D volumes of Ultrasound Data
  • Algorithm to maintain linear element in 3D Level Set Topology Optimization
  • Facial Expression recognition using Log-Euclidean statistical shape models.

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