In computer vision, we generally solve a classification problem by a single image. With the
video cameras being widely used in our real life, it is a nature choice to solve a classification …

In recent years, with the massive growth of data, the world today has entered the era of big
data. Big data has brought tremendous value to all fields of today's society, and it has also …

Text mining has become an increasingly significant role in processing medical information.
The research of text mining enhanced medical has attracted much attention in view from the …

Covariance descriptors (CovDs) for image set classification have been widely studied
recently. Different from the conventional CovDs, which describe similarities between pixels …

We present a powerful solution to the problem of vector set classification, based on a novel
goodness-of-fit metric, referred to as signal subspace matching (SSM). Unlike the existing …

Image set classification using manifolds is becoming increasingly more attractive since it
considers non-Euclidean geometry. However, with the success of dictionary learning for …

This paper proposes a framework for classifying motion sequences, by extending the
framework of Grassmann discriminant analysis (GDA). A problem of GDA is that its …

The increasing use of multiple sensors, which produce a large amount of multi-dimensional
data, requires efficient representation and classification methods. In this paper, we present a …

Smart contracts with automatic execution capability provide a vast development space for
transactions in Blockchain. However, due to the vulnerabilities in smart contracts, Blockchain …

This work presents a shallow network based on subspaces with applications in image
classification. Recently, shallow networks based on PCA filter banks have been employed to …