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

This paper presents the framework of kernel-based methods in the context of hyperspectral
image classification, illustrating from a general viewpoint the main characteristics of different …

随着模式识别, 机器学**, 遥感技术等相关学科领域的发展, 高光谱遥感影像分类研究取得快速
进展. 本文系统总结和评述了当前高光谱遥感影像分类的相关研究进展, 在总结分类策略的基础 …

This letter presents a framework of composite kernel machines for enhanced classification of
hyperspectral images. This novel method exploits the properties of Mercer's kernels to …

This paper introduces a semisupervised classification method that exploits both labeled and
unlabeled samples for addressing ill-posed problems with support vector machines (SVMs) …

Non-intrusive load monitoring (NILM) can monitor the status of electrical appliances on-line
and provide detailed power consumption data, which is the basis for customers to perform …

Earth observation is the field of science concerned with the problem of monitoring and
modeling the processes on the Earth surface and their interaction with the atmosphere. The …

Obtaining training data for land cover classification using remotely sensed data is time
consuming and expensive especially for relatively inaccessible locations. Therefore …

In remote-sensing classification, there are situations when users are only interested in
classifying one specific land-cover type, without considering other classes. These situations …

This paper addresses classification of hyperspectral remote sensing images with kernel-
based methods defined in the framework of semisupervised support vector machines (S 3 …