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A multigradient algorithm using a mixture of experts architecture for land cover classification of multisensor images

Publication Type : Journal Article

Publisher : Taylor & Francis

Source : International Journal of Remote Sensing, Taylor & Francis, Volume 32, Issue 17, p.4933–4941 (2011)

Url : https://www.tandfonline.com/doi/abs/10.1080/01431161.2010.493564

Campus : Amritapuri

School : School of Arts and Sciences

Department : Mathematics

Year : 2011

Abstract : pAn algorithm for supervised classification of multisensor images is proposed. The mixture of experts (ME) architecture with dynamic weight allocation is used for multiclass classification. Here the classification is treated as a maximum likelihood problem and the synaptic weights of the expert network and gating network are updated by a stochastic multigradient approach. Data from an optical sensor with four bands and a synthetic aperture radar (SAR) image of the same scene has been fused and classified. The algorithm is compared to some other advanced training algorithms in the literature for the same image data. © 2011 Taylor amp; Francis./p

Cite this Research Publication : Pramod P. Nair, “A multigradient algorithm using a mixture of experts architecture for land cover classification of multisensor images”, International Journal of Remote Sensing, vol. 32, no. 17, pp. 4933–4941, 2011.

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