Buch, Englisch, 157 Seiten, Format (B × H): 152 mm x 229 mm, Gewicht: 380 g
Buch, Englisch, 157 Seiten, Format (B × H): 152 mm x 229 mm, Gewicht: 380 g
ISBN: 978-0-444-64205-9
Verlag: Elsevier Science & Technology
Zielgruppe
<p>Research scientists and graduate students specialising in mathematics, as well as engineers with a basic knowledge in partial differential equations and their numerical approximations.</p>
Fachgebiete
Weitere Infos & Material
Section One 1. Compressed Learning for Image Classification: A Deep Neural Network Approach E. Zisselman, A. Adler and M. Elad
Section Two 2. Exploiting the Structure Effectively and Efficiently in Low Rank Matrix Recovery Jian-Feng Cai and Ke Wei
Section Three 3. Partial Single- and Multi-Shape Dense Correspondence Using Functional Maps Alex Bronstein 4. Shape Correspondence and Functional Maps Maks Ovsjanikov 5. Factoring Scene Layout From Monocular Images in Presence of Occlusion Niloy J. Mitra