Semi-Supervised Deep Kernel Active Learning for Material Removal Rate Prediction in Chemical Mechanical Planarization

The material removal rate (MRR) is an important variable but difficult to measure in the chemical–mechanical planarization (CMP) process. Most data-based virtual metrology (VM) methods ignore the large number of unlabeled samples, resulting in a waste of information. In this paper, the semi-supervis...

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Detalles Bibliográficos
Autores principales: Lv, Chunpu, Huang, Jingwei, Zhang, Ming, Wang, Huangang, Zhang, Tao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10181745/
https://www.ncbi.nlm.nih.gov/pubmed/37177595
http://dx.doi.org/10.3390/s23094392

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10181745/
https://www.ncbi.nlm.nih.gov/pubmed/37177595
http://dx.doi.org/10.3390/s23094392

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