Deep neural network (DNN) has been used as a learning model for modeling the
hierarchical architecture of human brain. However, DNN suffers from problems of learning …

Collaborative representation is an effective way to design classifiers for many practical
applications. In this paper, we propose a novel classifier, called the prior knowledge-based …

In order to extract invariant features in the palmprint transformation of scale, rotation and
affine distortion, a coarse-to-fine palmprint recognition method is proposed by combining the …

Plant recognition is one of important research areas of pattern recognition. As plant leaves
are extremely irregular, complex and diverse, many existing plant classification and …

Spectrum analysis can quickly extract and analyze frequency domain features of signal, and
it has been widely applied in fields of image processing, noise processing and signal …

In this article we propose several two-phase representation-based classification (RBC)
methods that are inspired by the idea of the two-phase test sample sparse representation …

This paper give an overview of current Facial Emotion Recognition (FER) stages,
techniques, and datasets. FER has been recognized for a decades and it is a vital topic in …

The paper presents a dictionary integration algorithm using 3D morphable face models
(3DMM) for pose-invariant collaborative-representation-based face classification. To this …

Sparse representation, which uses a test sample to represent a linear combination of an
entire set of training samples, has achieved great success in face recognition, and it results …

There has been a dramatic growth in the number and range of Internet of Things (IoT)
sensors that generate healthcare data. These sensors stream high-dimensional time series …