Measurement of Froth-Layer Depth With Binocular Camera Based on Intensity Correction and Its Application to Pulp-Grade Monitoring
Author:
Affiliation:
1. School of Automation, Central South University, Changsha, China
2. School of Mathematics and Statistics, Central South University, Changsha, China
Funder
National Natural Science Foundation of China
Natural Science Foundation of Hunan Province
Key Projects of NSFC
Key-Area Research and Development Program of Guangdong
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Link
http://xplorestaging.ieee.org/ielx8/19/10367905/10577089.pdf?arnumber=10577089
Reference33 articles.
1. Operating Condition Recognition in Zinc Flotation Using Statistic and Temporal Correlation Features
2. Disturbance-Encoding-Based Neural Hammerstein–Wiener Model for Industrial Process Predictive Control
3. A layered working condition perception integrating handcrafted with deep features for froth flotation
4. Data-driven flotation reagent changing evaluation via union distribution analysis of bubble size and shape
5. Grouped Time Series Networks for Grade Monitoring of Zinc Tailings With Multisource Features
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