Land-cover map** in remote sensing (RS) applications renders rich information for
decision support and environmental monitoring systems. The derivation of such information …

Driven by key law enforcement and commercial applications, research on face recognition
from video sources has intensified in recent years. The ensuing results have demonstrated …

In this paper we propose a discriminant learning framework for problems in which data
consist of linear subspaces instead of vectors. By treating subspaces as basic elements, we …

Many small online retailers and new entrants to the online retail sector are keen to practice
data mining and consumer-centric marketing in their businesses yet technically lack the …

Hierarchical classification learning, which organizes data categories into a hierarchical
structure, is an effective approach for large-scale classification tasks. The high …

In this paper, we examine image and video-based recognition applications where the
underlying models have a special structure-the linear subspace structure. We discuss how …

Many modern applications of signal processing and machine learning, ranging from
computer vision to computational biology, require the analysis of large volumes of high …

Introduction Structural MRI has long been used to characterize local morphological features
of the human brain. Coordination patterns of the local morphological features among …

We focus on the distribution regression problem: regressing to vector-valued outputs from
probability measures. Many important machine learning and statistical tasks fit into this …

Classical face recognition techniques have been successful at operating under well-
controlled conditions; however, they have difficulty in robustly performing recognition in …