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Reducing the Learning Population Size for Morphological Classification of Natural Materials: Example of Gold Grains from Backscattered Electron Images

Published online by Cambridge University Press:  01 August 2018

Alexandre Néron
Affiliation:
IOS Services Géoscientifiques Inc., Saguenay, Canada
Réjean Girard
Affiliation:
IOS Services Géoscientifiques Inc., Saguenay, Canada
Jonathan Tremblay
Affiliation:
IOS Services Géoscientifiques Inc., Saguenay, Canada
L. Paul Bédard
Affiliation:
LabMaTer, Sciences de la Terre, Université du Québec à Chicoutimi, Saguenay, Canada
Kevin Bouchard
Affiliation:
Université du Québec à Chicoutimi, Computer Department, Saguenay, Canada
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Abstract

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© Microscopy Society of America 2018 

References

[1] DiLabio, R.N.W. Geological Survey of Canada 90-1C 1990) p. 323329.Google Scholar
[2] Pan, S.J. Yang, Q. IEEE Transactions on knowledge and data engineering 22.10 2010) p. 13451359.CrossRefGoogle Scholar
[3] Szegedy, C., et al., IEEE Conference on Computer Vision and Pattern Recognition 2016.Google Scholar
[4] Abadi, M., et al., OSDI 16 2016.Google Scholar
[5] The authors acknowledge funding from Fonds de recherche Quebec Nature et Technologies (Projet de recherche orientee en partenariat) to LPB. Vincent Tao, Sanmei Gao and Phillipe Page, are thanked for their contributions to this work.Google Scholar

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Reducing the Learning Population Size for Morphological Classification of Natural Materials: Example of Gold Grains from Backscattered Electron Images
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