bullet Sensors & Transducers Journal

    (ISSN: 2306-8515, e-ISSN 1726-5479)

205.767

2008 e-Impact Factor

25 Top Downloaded Articles

Best Selling Articles 2012

Journal Subscription 2014

Editorial Calendar

Submit an Article

Editorial Board

Current Issue

S&T journal's cover

Sensors & Transducers Journal 2011

Sensors & Transducers Journal 2010

Sensors & Transducers Journal 2009

Sensors & Transducers Journal 2008

Sensors & Transducers Journal 2007

2000-2002 S&T e-Digest Contents

2003 S&T e-Digest Contents

2004 S&T e-Digest Contents

2005 S&T e-Digest Contents

2006 S&T e-Digest Contents

 

Best Articles 2011

 

 

 

Vol. 168, Issue 4, April 2014, pp. 23-29

 

Bullet

 

Remote Sensing Image Classification by Bayesian Network Classifier Based on Causality
 

1 Wang Qiuquan, 2 Guo Li, 3 Li Xiang

1 West Section Headquarters, China Transportation Construction Co., Ltd., Xian, 710065, China
2 School of Economics and Management, China University of Geosciences, Wuhan, 430074, China
3 School of Computer, China University of Geosciences, Wuhan, 430074, China
1 Tel.:15991169521

E-mail: lixiang@cug.edu.cn

 

Received: 25 December 2013 /Accepted: 28 February 2014 /Published: 30 April 2014

Digital Sensors and Sensor Sysstems

 

Abstract: It has always been a hotspot and difficult point in remote sensing to identify interesting geographical objects from remote sensing images. To reduce the independence between the random variables in the network Bayesian classifier model and to improve the classification performance, a causality-based network Bayesian classifier is suggested in this paper. In this model, the improved genetic algorithm is used for network topology learning and causality analyzing is taken for feature selection, which aims to realizing automatic recognition of unfavorable geological bodies. Experiments show that this model is of good classification performance and of high classification stability.

 

Keywords: Remote sensing, Bayesian network, Genetic algorithm, Adverse geological.

 

Acrobat reader logo Click <here> or title of paper to download the full pages article in pdf format

 

 

Subscribe the full-page Sensors & Transducers journal in print (paper) or pdf formats

(shipping cost by standard mail for paper version is included)

(25 % discount for IFSA Members)

 

 

 

Alternatively we accept a money transfer to our bank account. Please contact for details: sales@sensorsportal.com

 

 

Download <here> the Library Journal Recommendation Form

 

 

 

 

 


1999 - 2014 Copyright , International Frequency Sensor Association (IFSA) Publishing, S.L. All Rights Reserved.


Home - News - Links - Archives - Tools - Voltage-to-Frequency Converters - Standardization - Patents - Marketplace - Projects - Wish List - e-Shop - Sensor Jobs - Membership - Videos - Publishing - Site Map - Subscribe - Search

 Members Area -Sensors Portal -Training Courses - S&T Digest - For advertisers - Bookstore - Forums - Polls - Submit Press Release - Submit White Paper - Testimonies - Twitter - Facebook - LinkedIn