Texture classification is used in various pattern recognition applications that possess feature-
liked appearance. This paper aims to compile the recent trends on the usage of feature …

Wood species recognition is a texture classification problem that has yet to be well studied.
The textures observed on the cross section surface of the wood samples can be used to …

Texture classification is used in various pattern recognition applications that possess feature-
liked Appearance. This paper aims to compile the recent trends on the usage of feature …

The symmetric positive-definite (SPD) matrix, as a connected Riemannian manifold, has
become increasingly popular for encoding image information. Most existing sparse models …

In recent years, there has been extensive research on sparse representation of vector-
valued signals. In the matrix case, the data points are merely vectorized and treated as …

This paper advocates a novel framework for segmenting a dataset on a Riemannian
manifold M into clusters lying around low-dimensional submanifolds of M. Important …

In this study, 65 kinds of wood samples were classified by using artificial neural networks
based on the measured value of wood thermal physical parameters. First, the thermal …

Metric learning has been shown to be highly effective to improve the performance of nearest
neighbor classification. In this paper, we address the problem of metric learning for …

This paper advocates a novel framework for segmenting a dataset in a Riemannian manifold
M into clusters lying around low-dimensional submanifolds of M. Important examples of M …

In this paper, a novel signal detector based on matrix information geometric dimensionality
reduction (DR) is proposed, which is inspired from spectrogram processing. By short time …