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Remote Sensing Image Classification using Back Propogation

Published on December 2014 by Shah Kehul, More S A
journal_cover_thumbnail

National Conference on Advances in Communication and Computing
Foundation of Computer Science USA
NCACC2014 - Number 2
December 2014
Authors: Shah Kehul, More S A
a89c2cd2-6c17-4c0c-89b8-e0bc4efa2f7c

Shah Kehul, More S A . Remote Sensing Image Classification using Back Propogation. National Conference on Advances in Communication and Computing. NCACC2014, 2 (December 2014), 9-11.

@article{
author = { Shah Kehul, More S A },
title = { Remote Sensing Image Classification using Back Propogation },
journal = { National Conference on Advances in Communication and Computing },
issue_date = { December 2014 },
volume = { NCACC2014 },
number = { 2 },
month = { December },
year = { 2014 },
issn = 0975-8887,
pages = { 9-11 },
numpages = 3,
url = { /proceedings/ncacc2014/number2/19126-2011/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 National Conference on Advances in Communication and Computing
%A Shah Kehul
%A More S A
%T Remote Sensing Image Classification using Back Propogation
%J National Conference on Advances in Communication and Computing
%@ 0975-8887
%V NCACC2014
%N 2
%P 9-11
%D 2014
%I International Journal of Computer Applications
Abstract

The resolution of remote sensing images increase every day . Most of the existing methods is used the same method for years. The existing method does not provide satisfactory result. The aim is to develop an artificial neural network based on classification method consists of segmentation and classification . Segmentation followed by K-Means method and then classification performed with back propagation neural network which provide accuracy and satisfactory result compare to the other method.

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Index Terms

Computer Science
Information Sciences

Keywords

Bp Network K-means Method Feature Extraction Segmenatation