Froth image analysis by use of transfer learning and convolutional neural networks

Author:

Fu Yihao,Aldrich ChrisORCID

Publisher

Elsevier BV

Subject

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

Reference47 articles.

1. Online monitoring and control of froth flotation systems with machine vision: A review;Aldrich;International Journal of Mineral Processing,2010

2. Aldrich, C., Smith, L.K., Verrelli, D.I., Bruckard, W.J., Kistner, M., 2017. Multivariate image analysis of a realgar-orpiment froth flotation system. Mineral Processing and Extractive Metallurgy Transactions C, Published online, Available at http://www.tandfonline.com/eprint/WqtEXXsDBrytc9JdXYzS/full.

3. Relationship between surface froth features and process conditions in the batch flotation of a sulphide ore;Aldrich;Miner. Eng.,1997

4. Aldrich, C., Smith, L.K., Verrelli, D.I., Bruckard, W.J., Kistner, M., Auret, L., 2014. Grade estimation in realgar-orpiment batch flotation systems by froth image analysis and kernel methods. In: Proceedings of the 27th International Minerals Processing Congress (IMPC 2014), Chapter 4, 14–22, Santiago, Chile, 20–24 October.

5. Random forests;Breiman;Mach. Learn.,2001

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