Support vector machines in remote sensing: A review
A wide range of methods for analysis of airborne-and satellite-derived imagery continues to
be proposed and assessed. In this paper, we review remote sensing implementations of …
be proposed and assessed. In this paper, we review remote sensing implementations of …
Hyperspectral image classification: Potentials, challenges, and future directions
Recent imaging science and technology discoveries have considered hyperspectral
imagery and remote sensing. The current intelligent technologies, such as support vector …
imagery and remote sensing. The current intelligent technologies, such as support vector …
Hyperspectral image classification with Markov random fields and a convolutional neural network
This paper presents a new supervised classification algorithm for remotely sensed
hyperspectral image (HSI) which integrates spectral and spatial information in a unified …
hyperspectral image (HSI) which integrates spectral and spatial information in a unified …
Comparison of support vector machine, neural network, and CART algorithms for the land-cover classification using limited training data points
Y Shao, RS Lunetta - ISPRS Journal of Photogrammetry and Remote …, 2012 - Elsevier
Support vector machine (SVM) was applied for land-cover characterization using MODIS
time-series data. Classification performance was examined with respect to training sample …
time-series data. Classification performance was examined with respect to training sample …
Advances in hyperspectral remote sensing of vegetation and agricultural crops
Hyperspectral data (Table 1) is acquired as continuous narrowbands (eg, each band with 1
to 10 nanometer or nm bandwidths) over a range of electromagnetic spectrum (eg, 400 …
to 10 nanometer or nm bandwidths) over a range of electromagnetic spectrum (eg, 400 …
[書籍][B] Fundamentals of satellite remote sensing: An environmental approach
E Chuvieco - 2020 - taylorfrancis.com
Fundamentals of Satellite Remote Sensing: An Environmental Approach, Third Edition, is a
definitive guide to remote sensing systems that focuses on satellite-based remote sensing …
definitive guide to remote sensing systems that focuses on satellite-based remote sensing …
Kernel-based methods for hyperspectral image classification
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 …
A survey of active learning algorithms for supervised remote sensing image classification
Defining an efficient training set is one of the most delicate phases for the success of remote
sensing image classification routines. The complexity of the problem, the limited temporal …
sensing image classification routines. The complexity of the problem, the limited temporal …
Composite kernels for hyperspectral image classification
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 …
Classification of hyperspectral images with regularized linear discriminant analysis
TV Bandos, L Bruzzone… - IEEE Transactions on …, 2009 - ieeexplore.ieee.org
This paper analyzes the classification of hyperspectral remote sensing images with linear
discriminant analysis (LDA) in the presence of a small ratio between the number of training …
discriminant analysis (LDA) in the presence of a small ratio between the number of training …