Phase boundary estimation in electrical resistance tomography with weighted multi-layer neural networks and front point approach

J. H. Kim; B. C. Kang; B. Y. Choi; S. H. Lee; M. C. Kim; B. S. Kim; K. Y. Kim; S. Kim

Phase boundary estimation in electrical resistance tomography with weighted multi-layer neural networks and front point approach

J. H. Kim, B. C. Kang, B. Y. Choi, S. H. Lee, M. C. Kim, B. S. Kim, K. Y. Kim, S. Kim

Division of Automotive Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

This work presents a complex boundary estimation approach in electrical impedance imaging for binary-mixture fields based on a weighted multi-layer neural network and front point approach. The interfacial boundary expressed with front points and the unknown front points are estimated with the weighted multi-layer neural netwrok. Results from numerical experiments show that the proposed approach is insensitive to the measurement noise and has a strong good possibility for application in the visualization of binary mixtures for real time monitoring.

Original language	English
Title of host publication	4th World Congress in Industrial Process Tomography
Publisher	International Society for Industrial Process Tomography
Pages	410-415
Number of pages	6
ISBN (Electronic)	9780853163206
State	Published - 2005
Event	4th World Congress in Industrial Process Tomography - Aizu, Japan Duration: 5 Sep 2005 → 5 Sep 2005

Publication series

Name	4th World Congress in Industrial Process Tomography

Conference

Conference	4th World Congress in Industrial Process Tomography
Country/Territory	Japan
City	Aizu
Period	5/09/05 → 5/09/05

Bibliographical note

Publisher Copyright:
© 2014 International Society for Industrial Process Tomography.

Keywords

Boundary estimation
Front point tracking
Multi-layer neural network

Cite this

Kim, J. H., Kang, B. C., Choi, B. Y., Lee, S. H., Kim, M. C., Kim, B. S., Kim, K. Y., & Kim, S. (2005). Phase boundary estimation in electrical resistance tomography with weighted multi-layer neural networks and front point approach. In 4th World Congress in Industrial Process Tomography (pp. 410-415). (4th World Congress in Industrial Process Tomography). International Society for Industrial Process Tomography.

@inproceedings{6c540d354d7b45cfa40d3516dfff5b87,

title = "Phase boundary estimation in electrical resistance tomography with weighted multi-layer neural networks and front point approach",

abstract = "This work presents a complex boundary estimation approach in electrical impedance imaging for binary-mixture fields based on a weighted multi-layer neural network and front point approach. The interfacial boundary expressed with front points and the unknown front points are estimated with the weighted multi-layer neural netwrok. Results from numerical experiments show that the proposed approach is insensitive to the measurement noise and has a strong good possibility for application in the visualization of binary mixtures for real time monitoring.",

keywords = "Boundary estimation, Front point tracking, Multi-layer neural network",

author = "Kim, {J. H.} and Kang, {B. C.} and Choi, {B. Y.} and Lee, {S. H.} and Kim, {M. C.} and Kim, {B. S.} and Kim, {K. Y.} and S. Kim",

note = "Publisher Copyright: {\textcopyright} 2014 International Society for Industrial Process Tomography.; 4th World Congress in Industrial Process Tomography ; Conference date: 05-09-2005 Through 05-09-2005",

year = "2005",

language = "English",

series = "4th World Congress in Industrial Process Tomography",

publisher = "International Society for Industrial Process Tomography",

pages = "410--415",

booktitle = "4th World Congress in Industrial Process Tomography",

}

Kim, JH, Kang, BC, Choi, BY, Lee, SH, Kim, MC, Kim, BS, Kim, KY & Kim, S 2005, Phase boundary estimation in electrical resistance tomography with weighted multi-layer neural networks and front point approach. in 4th World Congress in Industrial Process Tomography. 4th World Congress in Industrial Process Tomography, International Society for Industrial Process Tomography, pp. 410-415, 4th World Congress in Industrial Process Tomography, Aizu, Japan, 5/09/05.

Phase boundary estimation in electrical resistance tomography with weighted multi-layer neural networks and front point approach. / Kim, J. H.; Kang, B. C.; Choi, B. Y. et al.
4th World Congress in Industrial Process Tomography. International Society for Industrial Process Tomography, 2005. p. 410-415 (4th World Congress in Industrial Process Tomography).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Phase boundary estimation in electrical resistance tomography with weighted multi-layer neural networks and front point approach

AU - Kim, J. H.

AU - Kang, B. C.

AU - Choi, B. Y.

AU - Lee, S. H.

AU - Kim, M. C.

AU - Kim, B. S.

AU - Kim, K. Y.

AU - Kim, S.

PY - 2005

Y1 - 2005

N2 - This work presents a complex boundary estimation approach in electrical impedance imaging for binary-mixture fields based on a weighted multi-layer neural network and front point approach. The interfacial boundary expressed with front points and the unknown front points are estimated with the weighted multi-layer neural netwrok. Results from numerical experiments show that the proposed approach is insensitive to the measurement noise and has a strong good possibility for application in the visualization of binary mixtures for real time monitoring.

AB - This work presents a complex boundary estimation approach in electrical impedance imaging for binary-mixture fields based on a weighted multi-layer neural network and front point approach. The interfacial boundary expressed with front points and the unknown front points are estimated with the weighted multi-layer neural netwrok. Results from numerical experiments show that the proposed approach is insensitive to the measurement noise and has a strong good possibility for application in the visualization of binary mixtures for real time monitoring.

KW - Boundary estimation

KW - Front point tracking

KW - Multi-layer neural network

UR - http://www.scopus.com/inward/record.url?scp=84910136565&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:84910136565

T3 - 4th World Congress in Industrial Process Tomography

SP - 410

EP - 415

BT - 4th World Congress in Industrial Process Tomography

PB - International Society for Industrial Process Tomography

T2 - 4th World Congress in Industrial Process Tomography

Y2 - 5 September 2005 through 5 September 2005

ER -

Kim JH, Kang BC, Choi BY, Lee SH, Kim MC, Kim BS et al. Phase boundary estimation in electrical resistance tomography with weighted multi-layer neural networks and front point approach. In 4th World Congress in Industrial Process Tomography. International Society for Industrial Process Tomography. 2005. p. 410-415. (4th World Congress in Industrial Process Tomography).

Phase boundary estimation in electrical resistance tomography with weighted multi-layer neural networks and front point approach

Abstract

Publication series

Conference

Bibliographical note

Keywords

Other files and links

Fingerprint

Cite this