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LTGH: A Dynamic Texture Feature for Working Condition Recognition in the Froth Flotation.

, , , , and . IEEE Trans. Instrum. Meas., (2021)

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LTGH: A Dynamic Texture Feature for Working Condition Recognition in the Froth Flotation., , , , and . IEEE Trans. Instrum. Meas., (2021)Temperature Measurement and Compensation Method of Blast Furnace Molten Iron Based on Infrared Computer Vision., , , , , and . IEEE Trans. Instrum. Meas., 68 (10): 3576-3588 (2019)A Hybrid Control Strategy for Real-Time Control of the Iron Removal Process of the Zinc Hydrometallurgy Plants., , , , and . IEEE Trans. Ind. Informatics, 14 (12): 5278-5288 (2018)Multiobjective-Based Optimization and Control for Iron Removal Process Under Dynamic Environment., , , and . IEEE Trans. Ind. Informatics, 17 (1): 569-577 (2021)A Binocular Camera Calibration Method in Froth Flotation Based on Key Frame Sequences and Weighted Normalized Tilt Difference., , , , , and . IEEE Trans. Circuits Syst. Video Technol., 33 (10): 5576-5586 (October 2023)Unsupervised Monocular Depth Estimation with Semantic Reconstruction Using Dual-Discriminator Generative Adversarial., , , , and . ICONIP (7), volume 1961 of Communications in Computer and Information Science, page 396-406. Springer, (2023)Dual Cross-Attention Transformer Networks for Temporal Predictive Modeling of Industrial Process., , , and . IEEE Trans. Instrum. Meas., (2024)Multi-generator adversarial dynamic spatial-temporal shapelet network for anode effect prediction in aluminum electrolysis process., , , and . Adv. Eng. Informatics, (2024)Fuzzy association rule-based set-point adaptive optimization and control for the flotation process., , , , and . Neural Comput. Appl., 32 (17): 14019-14029 (2020)Hybrid-driven BRBCS-BOM with expert intervention and its application for abnormity recognition in electrolytic cell., , , , , and . Expert Syst. Appl., 238 (Part F): 122227 (March 2024)