It is well known that different frames play different roles in feature learning in video based
human action recognition task. However, most existing deep learning models put the same …

Locality and label information of training samples play an important role in image
classification. However, previous dictionary learning algorithms do not take the locality and …

Rice (Oryza sativa L.) is a major staple food worldwide, and is traded extensively. The
objective of this study is to distinguish the rice grains of 30 varieties nondestructively using …

Non-negative matrix factorization (NMF) has recently attracted much attention due to its
good interpretation in perception science and widely applications in various fields. In this …

Recent studies have demonstrated advantages of the representations learned by
Convolutional Neural Networks (CNNs) in providing an appealing paradigm for visual …

Recently convolutional neural networks (CNN) have demonstrated remarkable performance
in various classification problems. In this paper, we also introduce CNN into in-air …

Discriminative dictionary learning plays a key role in sparse representation-based
classification. In this paper, we propose a low-rank graph preserving discriminative …

Deep dictionary learning (DDL) shows good performance in visual classification tasks.
However, almost all existing DDL methods ignore the locality relationships between the …

Sparse manifold clustering and embedding (SMCE) adaptively selects neighbor points from
the same manifold and approximately spans a low-dimensional affine subspace, but it does …

A novel dictionary learning algorithm, namely reconstructive and discriminative dictionary
learning based on sparse representation classification criterion (RDDLSRCC), is proposed …