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VERSION:2.0
PRODID:-//University of Liverpool Computer Science Seminar System//v2//EN
BEGIN:VEVENT
DTSTAMP:20260921T211522Z
UID:Seminar-MIF-1377@lxserverM.csc.liv.ac.uk
ORGANIZER:CN=Othon Michail:MAILTO:Othon.Michail@liverpool.ac.uk
DTSTART:20220114T140000
DTEND:20220114T150000
SUMMARY:MIF Series
DESCRIPTION:Michael White: Digital Fingerprinting of Microstructures.\n\nA statistical framework is systematically developed for compressed characterisation of a population of images, which includes some classical computer vision methods as special cases. The focus is on materials microstructure. The ultimate purpose is to rapidly fingerprint sample images in the context of various high-throughput design/make/test scenarios. This includes, but is not limited to, quantification of the disparity between microstructures for quality control, classifying microstructures, predicting materials properties from image data and identifying potential processing routes to engineer new materials with specific properties. Here, we consider microstructure classification and utilise the resulting features over a range of related machine learning tasks, such as supervised, semi-supervised, and unsupervised learning.\n\nhttps://www.csc.liv.ac.uk/research/seminars/abstract.php?id=1377
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