Chapter Overview The diffusion in power systems of distributed renewable energy
resources, electric vehicles, and controllable loads has made advanced monitoring systems …

The performance of object detection has recently been significantly improved due to the
powerful features learnt through convolutional neural networks (CNNs). Despite the …

This book revolves around the question of designing a matrix D∈ Rm× n called dictionary,
such that to obtain good sparse representations y≈ Dx for a class of signals y∈ Rm given …

This paper proposes a new deep learning method, the greedy deep weighted dictionary
learning for mobile multimedia for medical diseases analysis. Based on the traditional …

Attributes are human describable features, which have been used successfully for face,
object, and activity recognition. Facial attributes are intuitive descriptions of faces and have …

For sparse representation or sparse coding based image classification, the dictionary, which
is required to faithfully and robustly represent query images, plays an important role on its …

Abstract The Multiple Instance Hybrid Estimator for discriminative target characterization
from imprecisely labeled hyperspectral data is presented. In many hyperspectral target …

Domain adaptation has been a primal approach to addressing the issues by lack of labels in
many data mining tasks. Although considerable efforts have been devoted to domain …

In this paper, we propose a new nonlinear dictionary learning (NDL) method and apply it to
image classification. While a variety of dictionary learning algorithms have been proposed in …

In this paper, we propose a novel semi-supervised learning framework for violence detection
in video surveillance. With this framework, a classifier which distinguishes violent behavior …