All in-text references underlined in blue are linked to publications on ResearchGate, letting you access and read them immediately
One of the most important functions of remote sensing data is the production of Land Use and Land Co...
Land cover information is essential for many diverse applications. Various natural resource manageme...
Abstract—Satellite imagery classification using the support vector machine (SVM) algorithm may be a ...
A linear support vector machine (LSVM) is based on deter-mining an optimum hyperplane that separates...
Remote sensing is collecting information about an object without any direct physical contact with th...
Abstract — This paper includes a prospective approach of developing an efficient algorithm for class...
A wide range of methods for analysis of airborne- and satellite-derived imagery continues to be prop...
This chapter presents an extensive and critical review on the use of kernel methods and in particula...
In the last decade, the application of statistical and neural network classifiers to re...
Classification of broad area features in satellite imagery is one of the most important applications...
The classification of remote sensing images is a challenging task, as image contains bulk of informa...
This paper proposed a remote sensing image classification method based on Support Vector Machine (SV...
Abstract. Imaging spectroscopy, also known as hyperspectral remote sensing, is concerned with the me...
In this paper, a novel context-sensitive classification technique based on Support Vector Machines (...
In this work, we present a new support vector machine (SVM)-based active learning method for the cla...
One of the most important functions of remote sensing data is the production of Land Use and Land Co...
Land cover information is essential for many diverse applications. Various natural resource manageme...
Abstract—Satellite imagery classification using the support vector machine (SVM) algorithm may be a ...
A linear support vector machine (LSVM) is based on deter-mining an optimum hyperplane that separates...
Remote sensing is collecting information about an object without any direct physical contact with th...
Abstract — This paper includes a prospective approach of developing an efficient algorithm for class...
A wide range of methods for analysis of airborne- and satellite-derived imagery continues to be prop...
This chapter presents an extensive and critical review on the use of kernel methods and in particula...
In the last decade, the application of statistical and neural network classifiers to re...
Classification of broad area features in satellite imagery is one of the most important applications...
The classification of remote sensing images is a challenging task, as image contains bulk of informa...
This paper proposed a remote sensing image classification method based on Support Vector Machine (SV...
Abstract. Imaging spectroscopy, also known as hyperspectral remote sensing, is concerned with the me...
In this paper, a novel context-sensitive classification technique based on Support Vector Machines (...
In this work, we present a new support vector machine (SVM)-based active learning method for the cla...
One of the most important functions of remote sensing data is the production of Land Use and Land Co...
Land cover information is essential for many diverse applications. Various natural resource manageme...
Abstract—Satellite imagery classification using the support vector machine (SVM) algorithm may be a ...
DOI
Add to ORKG