A k-Shot Learning Approach to Recognition of Flotation Froth Conditions with Convolutional Neural Networks
Author:
Funder
Australian Research Council
Government of Western Australia
Australian Government
Publisher
Elsevier BV
Subject
General Medicine
Reference20 articles.
1. Multivariate image analysis of a realgar-orpiment froth flotation system;Aldrich;Mineral Processing and Extractive Metallurgy Transactions C,2018
2. Relationship between surface froth features and process conditions in the batch flotation of a sulphide ore;Aldrich;Minerals Engineering,1997
3. Laso: Label-set operations networks for multi-label few-shot learning;Alfassy,2019
4. Characterization of the flotation froth structure and color by machine vision (ChaCo);Bonifazi;Developments in Mineral Processing,2000
5. Characterisation of flotation froth colour and structure by machine vision;Bonifazi;Computers & Geosciences,2001
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