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dc.contributor.authorAwange, Joseph
dc.contributor.authorPaláncz, B.
dc.contributor.authorVölgyesi, L.
dc.date.accessioned2021-11-18T04:15:05Z
dc.date.available2021-11-18T04:15:05Z
dc.date.issued2019
dc.identifier.urihttp://hdl.handle.net/20.500.11937/86494
dc.identifier.doi10.1007/978-3-030-26153-5
dc.description.abstract

The book introduces the latest methods and algorithms developed in machine and deep learning (hybrid symbolic-numeric computations, robust statistical techniques for clustering and eliminating data as well as convolutional neural networks) dealing not only with images and the use of computers, but also their applications to visualization tasks generalized by up-to-date points of view. Associated algorithms are deposited on iCloud.

dc.publisherSpringer
dc.titleHybrid imaging and visualization: Employing machine learning with Mathematica - Python
dc.typeBook
dcterms.source.startPage1
dcterms.source.endPage411
dcterms.source.isbn9783030261528
dcterms.source.placeCham
dc.date.updated2021-11-18T04:15:04Z
curtin.departmentSchool of Earth and Planetary Sciences (EPS)
curtin.accessStatusFulltext not available
curtin.facultyFaculty of Science and Engineering
curtin.contributor.orcidAwange, Joseph [0000-0003-3533-613X]
curtin.contributor.researcheridAwange, Joseph [A-3998-2008]
curtin.contributor.scopusauthoridAwange, Joseph [6603092635]


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