Imaging, Vision and Learning Based on Optimization and PDEs IVLOPDE, Bergen, Norway, August 29 - September 2, 2016 /

This volume presents the peer-reviewed proceedings of the international conference Imaging, Vision and Learning Based on Optimization and PDEs (IVLOPDE), held in Bergen, Norway, in August/September 2016. The contributions cover state-of-the-art research on mathematical techniques for image processin...

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Bibliographic Details
Format: Electronic eBook
Language:English
Published: Cham : Springer International Publishing, 2018.
Edition:1st ed. 2018.
Series:Mathematics and Visualization,
Subjects:
Optical data processing.
Pattern recognition.
Computer mathematics.
Mathematical optimization.
Partial differential equations.
Computer graphics.
ISBN:9783319912745
ISSN:1612-3786
Online Access: Get full text
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Table of Contents:
  • Part I Image Reconstruction from Incomplete Data: 1 Adaptive Regularization for Image Reconstruction from Subsampled Data: M. Hintermüller et al
  • 2 A Convergent Fixed-Point Proximity Algorithm Accelerated by FISTA for the l_0 Sparse Recovery Problem: X. Zeng et al
  • 3 Sparse-Data Based 3D Surface Reconstruction for Cartoon and Map: B. Wu et al
  • Part II Image Enhancement, Restoration and Registration: 4 Variational Methods for Gamut Mapping in Cinema and Television: S. Waqas Zamir et al
  • 5 Functional Lifting for Variational Problems with Higher-Order Regularization: B. Loewenhauser et al
  • 6 On the Convex Model of Speckle Reduction: F. Fang et al
  • Part III 3D Image Understanding and Classification: 7 Multi-Dimensional Regular Expressions for Object Detection with LiDAR Imaging: T.C. Torgersen et al
  • 8 Relaxed Optimisation for Tensor Principal Component Analysis and Applications to Recognition, Compression and Retrieval of Volumetric Shapes: H. Itoh et al
  • Part IV Machine Learning and Big Data Analysis: 9 An Incremental Reseeding Strategy for Clustering: X. Bresson et al
  • 10 Ego-Motion Classification for Body-Worn Videos: Z. Meng et al
  • 11 Synchronized Recovery Method for Multi-Rank Symmetric Tensor Decomposition: H. Liu
  • Index.

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