Studying the Impact of Feature Saliency for Geoscientific Target Detection using Electroencephalography (EEG)

Accuracy and efficiency in geoscientific data interpretation is critically important for the resource industry, as based on these interpretations, significant financial decisions are made for exploration and extraction of resources. This study aims to understand image characteristics that impact int...

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Main Authors: Sivarajah, Y., Holden, E., Kovesi, P., Togneri, R., Tan, Tele, Price, G.
Other Authors: Geoff West, Peter Kovesi
Format: Conference Paper
Published: Institute of Electrical and Electronics Engineers 2012
Online Access:http://hdl.handle.net/20.500.11937/28379
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author Sivarajah, Y.
Holden, E.
Kovesi, P.
Togneri, R.
Tan, Tele
Price, G.
author2 Geoff West, Peter Kovesi
author_facet Geoff West, Peter Kovesi
Sivarajah, Y.
Holden, E.
Kovesi, P.
Togneri, R.
Tan, Tele
Price, G.
author_sort Sivarajah, Y.
building Curtin Institutional Repository
collection Online Access
description Accuracy and efficiency in geoscientific data interpretation is critically important for the resource industry, as based on these interpretations, significant financial decisions are made for exploration and extraction of resources. This study aims to understand image characteristics that impact interpreters' ability to detect geological targets within magnetic geophysics images. We use the Brain Computer Interface (BCI) approach to profile interpreter's neurological responses to geophysical target images using electroencephalography (EEG). These results are compared with image saliency analysis outputs, specifically the spatial distribution of visual attention peaks. Our experimental results showed that images with a wider dispersion of saliency lead to a lower rate of target detection based on EEG activities of interpreters.
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institution Curtin University Malaysia
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last_indexed 2025-11-14T08:09:55Z
publishDate 2012
publisher Institute of Electrical and Electronics Engineers
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spelling curtin-20.500.11937-283792017-09-13T15:19:08Z Studying the Impact of Feature Saliency for Geoscientific Target Detection using Electroencephalography (EEG) Sivarajah, Y. Holden, E. Kovesi, P. Togneri, R. Tan, Tele Price, G. Geoff West, Peter Kovesi Accuracy and efficiency in geoscientific data interpretation is critically important for the resource industry, as based on these interpretations, significant financial decisions are made for exploration and extraction of resources. This study aims to understand image characteristics that impact interpreters' ability to detect geological targets within magnetic geophysics images. We use the Brain Computer Interface (BCI) approach to profile interpreter's neurological responses to geophysical target images using electroencephalography (EEG). These results are compared with image saliency analysis outputs, specifically the spatial distribution of visual attention peaks. Our experimental results showed that images with a wider dispersion of saliency lead to a lower rate of target detection based on EEG activities of interpreters. 2012 Conference Paper http://hdl.handle.net/20.500.11937/28379 10.1109/DICTA.2012.6411707 Institute of Electrical and Electronics Engineers restricted
spellingShingle Sivarajah, Y.
Holden, E.
Kovesi, P.
Togneri, R.
Tan, Tele
Price, G.
Studying the Impact of Feature Saliency for Geoscientific Target Detection using Electroencephalography (EEG)
title Studying the Impact of Feature Saliency for Geoscientific Target Detection using Electroencephalography (EEG)
title_full Studying the Impact of Feature Saliency for Geoscientific Target Detection using Electroencephalography (EEG)
title_fullStr Studying the Impact of Feature Saliency for Geoscientific Target Detection using Electroencephalography (EEG)
title_full_unstemmed Studying the Impact of Feature Saliency for Geoscientific Target Detection using Electroencephalography (EEG)
title_short Studying the Impact of Feature Saliency for Geoscientific Target Detection using Electroencephalography (EEG)
title_sort studying the impact of feature saliency for geoscientific target detection using electroencephalography (eeg)
url http://hdl.handle.net/20.500.11937/28379