NDLI: Clustering of spectral images using Echo state networks

Content Provider	IEEE Xplore Digital Library
Author	Koprinkova-Hristova, P. Angelova, D. Borisova, D. Jelev, G.
Copyright Year	2013
Description	Author affiliation: Inst. of Inf. & Commun. Technol., Sofia, Bulgaria (Koprinkova-Hristova, P.; Angelova, D.) \|\| Space Res. & Technol. Inst., Sofia, Bulgaria (Borisova, D.; Jelev, G.)
Abstract	In the present work we applied a recently developed procedure for multidimensional data clustering to processing of spectral satellite images. The core of our approach lays in projection of multidimensional image to a two dimensional one. The main aim is to discover points with similar characteristics. This was done by clustering of the resulting image. The processing technique exploits equilibrium states of a kind of recurrent neural network - Echo state network (ESN) - that are obtained after intrinsic plasticity (IP) tuning of the ESN using multidimensional data as inputs. The proposed in our previous work automated procedure for multidimensional data clustering is further refined and tested on the satellite image data. The obtained number and position of clusters of a multi-spectral image of a mountain region in Bulgaria is compared with the classification of the region landscape given by the Ministry of Regional Development and Public Works.
Sponsorship	IEEE Bulgaria Sect.
Starting Page	1
Ending Page	5
File Size	6261368
Page Count	5
File Format	PDF
ISBN	9781479906598
e-ISBN	9781479906611
DOI	10.1109/INISTA.2013.6577633
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-06-19
Publisher Place	Bulgaria
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Earth Satellites Neurons Satelite spectral image Echo state network Data clustering Reservoirs Vectors IP networks Remote sensing Intrinsic plasticity
Content Type	Text
Resource Type	Article

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