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Sýna 8 af 8 niðurstöðum (0.007 sekúndur)
Feature Selection Based on Hybridization of Genetic Algorithm and Particle Swarm Optimization
Ghamisi, Pedram; Benediktsson, Jon Atli (IEEE Geoscience & Remote Sensing Society, 2015-02)
A new feature selection approach that is based on the integration of a genetic algorithm and particle swarm optimization is proposed. The overall accuracy of a support vector machine classifier on validation samples is used as a fitness value. The new ...
Integration of Segmentation Techniques for Classification of Hyperspectral Images
Benediktsson, Jon Atli; Ghamisi, Pedram; Couceiro, Micael S.; Fauvel, Mathieu (IEEE, 2014)
A new spectral-spatial method for classification of hyperspectral images is introduced. The proposed approach is based on two segmentation methods, fractional-order Darwinian particle swarm optimization and mean shift segmentation. The output of these ...
Spectral-Spatial Hyperspectral Image Classification Using Subspace-Based Support Vector Machines and Adaptive Markov Random Fields
Benediktsson, Jon Atli; Yu, Haoyang; Gao, Lianru; Li, Jun; LI, Shan Shan; Zhang, Bing (Multidisciplinary Digital Publishing Institute, 2016)
This paper introduces a new supervised classification method for hyperspectral images that combines spectral and spatial information. A support vector machine (SVM) classifier, integrated with a subspace projection method to address the problems of ...
A Novel Evolutionary Swarm Fuzzy Clustering Approach for Hyperspectral Imagery
Ghamisi, Pedram; Ali, Abder-Rahman; Couceiro, Micael S.; Benediktsson, Jon Atli (IEEE, 2015)
In land cover assessment, classes often gradually change from one to another. Therefore, it is difficult to allocate sharp boundaries between different classes of interest. To overcome this issue and model such conditions, fuzzy techniques that resemble ...
A Novel Feature Selection Approach Based on FODPSO and SVM
Benediktsson, Jon Atli; Ghamisi, Pedram; Couceiro, Micael S. (IEEE, 2015-05)
A novel feature selection approach is proposed to address the curse of dimensionality and reduce the redundancy of hyperspectral data. The proposed approach is based on a new binary optimization method inspired by fractional-order Darwinian particle ...
Multilevel Image Segmentation Based on Fractional-Order Darwinian Particle Swarm Optimization
Benediktsson, Jon Atli; Ghamisi, Pedram; Martins, Fernando M. L.; Couceiro, Micael S. (IEEE, 2014)
Hyperspectral remote sensing images contain hundreds of data channels. Due to the high dimensionality of the hyperspectral data, it is difficult to design accurate and efficient image segmentation algorithms for such imagery. In this paper, a new ...
On Understanding Big Data Impacts in Remotely Sensed Image Classification Using Support Vector Machine Methods
Benediktsson, Jon Atli; Cavallaro, Gabriele; Riedel, Morris; Richerzhagen, Matthias; Plaza, Antonio (IEEE, 2015)
Owing to the recent development of sensor resolutions onboard different Earth observation platforms, remote sensing is an important source of information for mapping and monitoring natural and man-made land covers. Of particular importance is the ...
Spectral–Spatial Classification of Hyperspectral Images Based on Hidden Markov Random Fields
Benediktsson, Jon Atli; Úlfarsson, Magnús Örn; Ghamisi, Pedram (IEEE, 2014)
Hyperspectral remote sensing technology allows one to acquire a sequence of possibly hundreds of contiguous spectral images from ultraviolet to infrared. Conventional spectral classifiers treat hyperspectral images as a list of spectral measurements ...
Atriði 1-8 af 8
Benediktsson, Jon Atli (8)
Couceiro, Micael S. (4)
LI, Shan Shan (1)
Martins, Fernando M. L. (1)
Support vector machines (8)
Geophysical image processing (3)
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