Mathematical Methodologies in Pattern Recognition and Machine Learning
Springer-Verlag New York Inc.
978-1-4614-5075-7 (ISBN)
This book will be suitable for scientists and researchers in optimization, numerical methods, computer science, statistics and for differential geometers and mathematical physicists.
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.
Reihe/Serie | Springer Proceedings in Mathematics & Statistics ; 30 |
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Zusatzinfo | VIII, 196 p. |
Verlagsort | New York, NY |
Sprache | englisch |
Maße | 155 x 235 mm |
Themenwelt | Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik |
Mathematik / Informatik ► Mathematik ► Angewandte Mathematik | |
Schlagworte | Hierarchical Sparse Coding • ICPRAM 2012 • machine learning • pattern recognition • Support Vector Machines |
ISBN-10 | 1-4614-5075-6 / 1461450756 |
ISBN-13 | 978-1-4614-5075-7 / 9781461450757 |
Zustand | Neuware |
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