Generative adversarial network-based image-level optimal setpoint calculation for flotation reagents control

作者：

Highlights：

• Image-level setpoint for computer-vision-based flotation reagent control is investigated.

• A generative adversarial network-based setpoint calculation model is developed.

• The calculated setpoint can be intuitively evaluated by naked-eye observing.

• The calculated setpoint is control attainable by changing flotation reagents.

摘要

•Image-level setpoint for computer-vision-based flotation reagent control is investigated.•A generative adversarial network-based setpoint calculation model is developed.•The calculated setpoint can be intuitively evaluated by naked-eye observing.•The calculated setpoint is control attainable by changing flotation reagents.

论文关键词：Computer vision,Generative adversarial network,Setpoint calculation,Deep learning feature,Froth flotation

论文评审过程：Received 29 June 2020, Revised 15 January 2021, Accepted 27 February 2022, Available online 3 March 2022, Version of Record 4 March 2022.

论文官网地址：https://doi.org/10.1016/j.eswa.2022.116790