Nov 23, 2018 · The paper aims to extend pattern recognition methodologies based on PCA for vector spaces to those for multilinear data. First, we extend the ...
The paper aims to extend pattern recognition methodologies based on PCA for vector spaces to those for multilinear data. First, we extend the canonical angle ...
This study explores an approach for analysing the mirror (reflective) symmetry of 3D shapes with tensor based sparse decomposition.
We explore the orthogonal decomposition of tensors (also known as multidimensional arrays or n-way arrays) using two different definitions of orthogonality.
Missing: Shapes | Show results with:Shapes
伊東 隼人 · Discrimination of Volumetric Shapes Using Orthogonal Tensor Decomposition.
We explore the orthogonal decomposition of tensors (also known as multidimensional arrays or n-way arrays) using two di#erent definitions of orthogonality.
Missing: Volumetric Shapes
To solve these issues, in this paper, we propose a method named as Orthogonal basis-core extraction using Tensor Ring (OTR) that can facilitate better ...
Missing: Shapes | Show results with:Shapes
May 17, 2018 · This paper presents a new image hashing that is designed with tensor decomposition (TD), referred to as TD hashing, where image hash ...
Missing: Shapes | Show results with:Shapes
We explore the orthogonal decomposition of tensors (also known as multidimensional arrays or n-way arrays) using two dierent denitions of orthogonality.
Missing: Shapes | Show results with:Shapes
Oct 1, 2010 · This is achieved based on orthogonal or nonnegative tensor (multi-array) decompositions, and higher order (multilinear) discriminant analysis ( ...