Novel technique for the preparation and analysis of powder-based polished sections by automated optical mineralogy: Part 2 – Use of deep learning approach for transparent mineral detection

Author:

De Castro Benjamin,Benzaazoua Mostafa,Roychowdhury Soumali,Chopard Aurélie,Quintal Lauzon Francis,Plante Benoît

Publisher

Elsevier BV

Subject

Mechanical Engineering,Geotechnical Engineering and Engineering Geology,General Chemistry,Control and Systems Engineering

Reference38 articles.

1. QEMSCAN° (Quantitative Evaluation of Minerals by Scanning Electron Microscopy): capability and application to fracture characterization in geothermal systems Paper presented at the Proc, Thirty-Seventh Workshop on Geotherm Reserv Eng;Ayling,2012

2. Berrezueta, E., Ordonez-Casado, B., Bonilla, W., Banda, R., Castroviejo, R., Carrion, P., Puglla, S., (2016). Ore Petrography Using Optical Image Analysis: Application to Zaruma-Portovelo Deposit (Ecuador). Geosciences, 6(2), 30. Retrieved from ://WOS:000410144300014. doi:ARTN 30 10.3390/geosciences6020030.

3. Automated mineral identification by optical microscopy;Berry;Australasian Institute of Mining and Metallurgy Publication Series,2008

4. Bouzahzah, H., Califice, A., Benzaazoua, M., Mermillod-Blondin, R., Pirard, E., 2008. Modal analysis of mineral blends using optical image analysis versus X ray diffraction. Paper presented at the Proceedings of International Congress for Applied Mineralogy ICAM08, Brisbane, Australia. AusIMM.

5. Bouzahzah, H., Benzaazoua, M., Mermillod-Blondin, R., Pirard, E., 2015. A novel procedure for polished section preparation for automated mineralogy avoiding internal particle settlement. In: Paper presented at the Proceedings of the 12th International Congress for Applied Mineralogy (ICAM), Istanbul, Turkey.

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