%0 Conference Paper
%A Wardaya, P.D.
%A Ridha, S.
%D 2014
%F scholars:5309
%I Institute of Physics Publishing
%K Algorithms; Image segmentation; Neural networks; Pixels; Satellite imagery, Back propagation neural networks; Computational time; Google earths; Hidden layers; Image-based; Network-based; Training data, Houses, algorithm; artificial neural network; back propagation; data set; digital image; image analysis; image classification; pixel; residential location; satellite imagery; urban area
%N 1
%R 10.1088/1755-1315/18/1/012019
%T Neural network-based segmentation of satellite imagery for estimating house cluster of an urban settlement from Google Earth images
%U https://khub.utp.edu.my/scholars/5309/
%V 18
%X In this paper a backpropagation neural network is utilized to perform house cluster segmentation from Google Earth data. The algorithm is subjected to identify houses in the image based on the RGB pattern within each pixel. Training data is given through cropping selection for a target that is a house cluster and a non object. The algorithm assigns 1 to a pixel belong to a class of object and 0 to a class of non object. The resulting outcome, a binary image, is then utilized to perform quantification to estimate the number of house clusters. The number of the hidden layer is varying in order to find its effect to the neural network performance and total computational time. © Published under licence by IOP Publishing Ltd.
%Z cited By 1; Conference of 8th International Symposium of the Digital Earth, ISDE 2014 ; Conference Date: 26 August 2013 Through 29 August 2013; Conference Code:108166