Performance comparisons of particle swarm optimization, echo state neural network and genetic algorithm for vegetation segmentation

 
 
 
  • Abstract
  • Keywords
  • References
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  • Abstract


    This article presents the implementation of vegetation segmentation by using soft computing methods: particle swarm optimization (PSO), echostate neural network(ESNN) and genetic algorithm (GA). Multispectral image with the required band from Landsat 8 (5, 4, 3) and Landsat 7 (4, 3, 2) are used. In this paper, images from ERDAS format acquired by Landsat 7 ‘Paris.lan’ (band 4, band 3, Band 2) and image acquired from Landsat 8 (band5, band 4, band 3) are used. The soft computing algorithms are used to segment the plane-1(Near infra-red spectra) and plane 2(RED spectra). The monochrome of the two segmented images is compared to present performance comparisons of the implemented algorithms.


  • Keywords


    Particle Swarm Optimization, Echostate Neural Network, Genetic Algorithm, Vegetation Segmentation.

  • References


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Article ID: 9286
 
DOI: 10.14419/ijet.v7i1.1.9286




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