Corpus ID: 17067380

Image Classification using SOM and SVM Feature Extraction

@inproceedings{Shrivastava2014ImageCU,
  title={Image Classification using SOM and SVM Feature Extraction},
  author={Pragati Shrivastava and P. Singh and G. Shrivastava},
  year={2014}
}
Support Vector Machines (SVMs) are a relatively new supervised classification technique to the land cover mapping community.SVM are machine learning techniques that are used for segmentation and classification of medical pictures, as well as segmentation of white matter hyperintensities (WMH). Although there are various techniques implemented for the classification of image, here combinatorial method of clustering and classification. Here the feature extraction using SVM based training is… CONTINUE READING

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References

Publications referenced by this paper.
SHOWING 1-10 OF 38 REFERENCES
HIGH EFFICIENT CLASSIFICATION ON REMOTE SENSING IMAGES BASED ON SVM
  • 14
  • PDF
Classification of hyperspectral remote sensing images with support vector machines
  • 2,616
  • PDF
Fuzzy-Topology-Integrated Support Vector Machine for Remotely Sensed Image Classification
  • 23
  • PDF
Feature Fusion in Improving Object Class Recognition
  • 11
FUZZY SHELL-CLUSTERING AND APPLICATIONS TO CIRCLE DETECTION IN DIGITAL IMAGES
  • 201
Scene-Oriented Hierarchical Classification of Blurry and Noisy Images
  • 18
Remote sensing image classification development in the past decade
  • 11