relation: https://khub.utp.edu.my/scholars/5309/
title: Neural network-based segmentation of satellite imagery for estimating house cluster of an urban settlement from Google Earth images
creator: Wardaya, P.D.
creator: Ridha, S.
description: 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.
publisher: Institute of Physics Publishing
date: 2014
type: Conference or Workshop Item
type: PeerReviewed
identifier:   Wardaya, P.D. and Ridha, S.  (2014) Neural network-based segmentation of satellite imagery for estimating house cluster of an urban settlement from Google Earth images.  In: UNSPECIFIED.     
relation: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84902308428&doi=10.1088%2f1755-1315%2f18%2f1%2f012019&partnerID=40&md5=faf50934605bbd70c3b88a60fe85669c
relation: 10.1088/1755-1315/18/1/012019
identifier: 10.1088/1755-1315/18/1/012019