Remote Sensing Image Classification: A survey of support-vector-machine-based advanced techniques
U Maulik, D Chakraborty - IEEE Geoscience and Remote …, 2017 - ieeexplore.ieee.org
Land-cover map** in remote sensing (RS) applications renders rich information for
decision support and environmental monitoring systems. The derivation of such information …
decision support and environmental monitoring systems. The derivation of such information …
[PDF][PDF] 高光谱遥感影像分类研究进展
杜培军， 夏俊士， 薛朝辉， 谭琨， 苏红军， 鲍蕊 - 遥感学报, 2021 - ygxb.ac.cn
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 …
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 …
Kernel-based methods for hyperspectral image classification
G Camps-Valls, L Bruzzone - IEEE Transactions on Geoscience …, 2005 - ieeexplore.ieee.org
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 …
image classification, illustrating from a general viewpoint the main characteristics of different …
Composite kernels for hyperspectral image classification
G Camps-Valls, L Gomez-Chova… - … and remote sensing …, 2006 - ieeexplore.ieee.org
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 …
hyperspectral images. This novel method exploits the properties of Mercer's kernels to …
A novel transductive SVM for semisupervised classification of remote-sensing images
L Bruzzone, M Chi, M Marconcini - IEEE Transactions on …, 2006 - ieeexplore.ieee.org
This paper introduces a semisupervised classification method that exploits both labeled and
unlabeled samples for addressing ill-posed problems with support vector machines (SVMs) …
unlabeled samples for addressing ill-posed problems with support vector machines (SVMs) …
Non-intrusive load monitoring algorithm based on features of V–I trajectory
AL Wang, BX Chen, CG Wang, D Hua - Electric Power Systems Research, 2018 - Elsevier
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 …
and provide detailed power consumption data, which is the basis for customers to perform …
Remote sensing image processing
G Camps-Valls, D Tuia, L Gómez-Chova, S Jiménez… - 2011 - Springer
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 …
modeling the processes on the Earth surface and their interaction with the atmosphere. The …
An active learning approach to hyperspectral data classification
S Rajan, J Ghosh, MM Crawford - IEEE Transactions on …, 2008 - ieeexplore.ieee.org
Obtaining training data for land cover classification using remotely sensed data is time
consuming and expensive especially for relatively inaccessible locations. Therefore …
consuming and expensive especially for relatively inaccessible locations. Therefore …
A positive and unlabeled learning algorithm for one-class classification of remote-sensing data
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 …
classifying one specific land-cover type, without considering other classes. These situations …
Semisupervised classification of hyperspectral images by SVMs optimized in the primal
M Chi, L Bruzzone - IEEE Transactions on Geoscience and …, 2007 - ieeexplore.ieee.org
This paper addresses classification of hyperspectral remote sensing images with kernel-
based methods defined in the framework of semisupervised support vector machines (S 3 …
based methods defined in the framework of semisupervised support vector machines (S 3 …