Processing, Analyzing and Learning of Images, Shapes, and Forms: Part 1

Contemporary book on advanced developments in the field of learning processes in images, shapes and forms

Ron Kimmel (Volume editor), Xue-Cheng Tai (Volume editor)

9780444642059, Elsevier Science

Hardback, published 8 November 2018

157 pages
22.9 x 15.1 x 1.8 cm, 0.38 kg

"It ranges from a novel attempt to put deep learning within the framework of compressed sensing and sparse models, reconstruction of low rank matrices, shifting into learning geometry, shape representation that has the potential to migrate geometry analysis into that of deep learning, and pure geometric problems dealt in a novel, yet axiomatic, manner." --zbMATH

Processing, Analyzing and Learning of Images, Shapes, and Forms: Volume 19, Part One provides a comprehensive survey of the contemporary developments related to the analysis and learning of images, shapes and forms. It covers mathematical models as well as fast computational techniques, and includes new chapters on Alternating diffusion: a geometric approach for sensor fusion, Shape Correspondence and Functional Maps, Geometric models for perception-based image processing, Decomposition schemes for nonconvex composite minimization: theory and applications, Low rank matrix recovery: algorithms and theory, Geometry and learning for deformation shape correspondence, and Factoring scene layout from monocular images in presence of occlusion.

Section One 1. Compressed Learning for Image Classification: A Deep Neural Network Approach E. Zisselman, A. Adler and M. Elad

Subject Areas: Numerical analysis [PBKS]