Show simple item record

dc.contributor.authorFu, Yihao
dc.contributor.supervisorChris Aldrichen_US

The development of soft sensor technologies facilitates the characterization and modelling of complex systems in the mining and mineral processing industry. This thesis is aimed to investigate the state-of-the-art convolutional neural networks in the mineral processing and geometallurgy applications such as froth flotation system characterization, drill core recognition, and particle size segmentation. These results outperformed traditional multivariate image analysis methods by a significant margin.

dc.publisherCurtin Universityen_US
dc.titleCharacterization of Ore and Bulk Solid Systems by Use of Multivariate Image Analysis and Deep Learning Neural Networksen_US
curtin.departmentWASM: Minerals, Energy and Chemical Engineeringen_US
curtin.accessStatusFulltext not availableen_US
curtin.facultyScience and Engineeringen_US
curtin.contributor.orcidFu, Yihao [0000-0003-3379-7194]en_US

Files in this item


This item appears in the following Collection(s)

Show simple item record