Results 81 to 90 of about 1,842 (194)
Intrinsic Shape LDA With Application to Body Human Shapes Classification
ABSTRACT Advancements in 3D scanning and cloud infrastructure enable the acquisition and analysis of high‐density body surface datasets. In this work, we propose a novel methodology that extends linear discriminant analysis (LDA) to Kendall's shape space for the classification of 3D objects, specifically human body shapes.
Jorge Valero +3 more
wiley +1 more source
Cloud‐Plots for Spherical Data With Applications to Glaucoma and Gait Cyclograms
ABSTRACT In several biomedical contexts, the need for diagnostic analyses of data that is a set of directions in 2, 3, or higher dimensions arises, as for instance, when considering the relative movement of body parts like the limbs, or looking at anatomical orientations.
S. Rao Jammalamadaka, Ali H. Abuzaid
wiley +1 more source
Surface measure on, and the local geometry of, sub-Riemannian manifolds. [PDF]
Don S, Magnani V.
europepmc +1 more source
Kazdan–Warner obstructions for a fourth‐order boundary problem
Abstract We derive Kazdan–Warner type identities for the boundary problem of prescribing nonconstant interior Q$Q$ curvature and boundary T$T$ curvature on the upper hemisphere S+4${\mathbb {S}}^{4}_{+}$ by a conformal change of the standard metric.
Sergio Cruz‐Blázquez +1 more
wiley +1 more source
Geometry of Manifolds and Applications
This editorial presents 24 research articles published in the Special Issue entitled Geometry of Manifolds and Applications of the MDPI Mathematics journal, which covers a wide range of topics from the geometry of (pseudo-)Riemannian manifolds and their ...
Adara M. Blaga
doaj +1 more source
Inference for Gaussian Processes with Matérn Covariogram on Compact Riemannian Manifolds. [PDF]
Li D, Tang W, Banerjee S.
europepmc +1 more source
Mirror descent on Riemannian manifolds
Mirror Descent (MD) is a scalable first-order method widely used in large-scale optimization, with applications in image processing, policy optimization, and neural network training. This paper generalizes MD to optimization on Riemannian manifolds. In particular, we develop a Riemannian Mirror Descent (RMD) framework via reparameterization and further
Jiaxin Jiang, Lei Shi, Jiyuan Tan
openaire +2 more sources
Weinstein neighborhood theorems for stratified subspaces
Abstract By analogy with Weinstein's neighborhood theorem, we prove a uniqueness result for symplectic neighborhoods of a large family of stratified subspaces. This result generalizes existing constructions, for example, in the search for exotic Lagrangians.
Yael Karshon +2 more
wiley +1 more source
Almost-Riemannian manifolds do not satisfy the curvature-dimension condition. [PDF]
Magnabosco M, Rossi T.
europepmc +1 more source
An EZ${\mathcal {E}\mathcal {Z}}$‐structure for the mapping class group
Abstract We construct a boundary for the mapping class group Mod(S)${\rm Mod}(S)$ of a surface S$S$ of finite type. The action of Mod(S)${\rm Mod}(S)$ on this boundary is minimal, strongly proximal and topologically free. The boundary is the boundary of an EZ${\mathcal {E}\mathcal {Z}}$‐structure for Mod(S)${\rm Mod}(S)$.
Ursula Hamenstädt
wiley +1 more source

