Smart Soft Sensor for Froth flotation quality monitoring using pre-trained feature extractor and Vision Transformer ViT-Reference-Cited by-同舟云学术

Smart Soft Sensor for Froth flotation quality monitoring using pre-trained feature extractor and Vision Transformer ViT

Published:2023-11-08 Issue: Volume: Page:
ISSN:
Container-title:2023 17th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS)
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Author:

Hasidi Oussama¹,Bendaouia Ahmed¹,Abdelwahed El Hassan²,Abdellah El Alaoui-Chrifi Moulay³,Boussetta Abdelmalek³,Benzakour Intissar³,Bourzeix François⁴,Oubouhss Kaotar⁵

Affiliation:

1. Mohammed VI Polytechnic University,LISI Laboratory, Computer Science Departement, UCA Analytics Lab,Marrakech,Morocco

2. Cadi Ayyad University,LISI Laboratory, Computer Science Departement,Marrakech,Morocco

3. Reminex, Managem Group,R&D and Engineering center,Marrakech,Morocco

4. Mohammed VI Polytechnic University,Analytics Lab,Rabat,Morocco

5. National School of Applied Science, UAE,Department of Electrical and Industrial Engineering,Tangier,Morocco

Funder

Ministry of Higher Education

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10472709/10472788/10472800.pdf?arnumber=10472800

Reference20 articles.

1. Disruptive Innovation in Mining Industry 4.0

2. Effects of influent physicochemical characteristics on air dissolution, bubble size and rise velocity in dissolved air flotation: A review

3. Recent advances in flotation froth image analysis

4. Soft computing-based modeling of flotation processes – A review

5. Data-driven flotation reagent changing evaluation via union distribution analysis of bubble size and shape

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