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BALANCED VS IMBALANCED TRAINING DATA:CLASSIFYING RAPIDEYE DATA WITH SUPPORT VECTOR MACHINES
Land cover classification Imbalanced training data Support Vector Machines RapidEye Agriculture
2016/11/23
The accuracy of supervised image classification is highly dependent upon several factors such as the design of training set (sample selection, composition, purity and size), resolution of input imager...
LAND COVER CLASSIFICATION FROM FULL-WAVEFORM LIDAR DATA BASED ON SUPPORT VECTOR MACHINES
LiDAR Support Vector Machines (SVM) Full-Waveform Land Cover Classification Waveform decomposition Feature extraction
2016/7/27
In this study, a land cover classification method based on multi-class Support Vector Machines (SVM) is presented to predict the types of land cover in Miyun area. The obtained backscattered full-wave...
ANALYSIS OF THE TRANSFERABILITY OF SUPPORT VECTOR MACHINES FOR VEGETATION CLASSIFICATION
Remote Sensing Mapping Classification Accuracy High resolution Ikonos
2015/12/31
This paper reports on research analysing the potential of Support Vector Machines (SVMs) for mapping vegetation from high spatial resolution Ikonos imagery. The work investigated the utility of SVMs f...
MODEL-BASED ESTIMATION OF IMPERVIOUS SURFACE BY APPLICATION OF SUPPORT VECTOR MACHINES
Urban Automation Modeling Impervious Surface Spatial Planning
2015/12/26
Due to its various negative consequences impervious surface is increasingly recognized as a key issue in assessing the sustainability of land use - particularly in urban environments. In Germany, a re...
FUSION OF IMAGING SPECTROMETER AND LIDAR DATA USING SUPPORT VECTOR MACHINES FOR LAND COVER CLASSIFICATION IN THE CONTEXT OF FOREST FIRE MANAGEMENT
Support Vector Machines land cover classification hyperspectral
2015/9/8
A combination of the two remote sensing systems, imaging spectrometry (IS) and Light Detection And Ranging (LiDAR), is well
suited to map fuel types, especially within the complex wildland urban inte...