Hybrid imaging and visualization: Employing machine learning with Mathematica - Python
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 a...
| Main Authors: | , , |
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| Format: | Book |
| Published: |
Springer
2019
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| Online Access: | http://hdl.handle.net/20.500.11937/86494 |
| _version_ | 1848764838140968960 |
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| author | Awange, Joseph Paláncz, B. Völgyesi, L. |
| author_facet | Awange, Joseph Paláncz, B. Völgyesi, L. |
| author_sort | Awange, Joseph |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | 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. |
| first_indexed | 2025-11-14T11:25:43Z |
| format | Book |
| id | curtin-20.500.11937-86494 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T11:25:43Z |
| publishDate | 2019 |
| publisher | Springer |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-864942021-11-29T03:37:31Z Hybrid imaging and visualization: Employing machine learning with Mathematica - Python Awange, Joseph Paláncz, B. Völgyesi, L. 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. 2019 Book http://hdl.handle.net/20.500.11937/86494 10.1007/978-3-030-26153-5 Springer restricted |
| spellingShingle | Awange, Joseph Paláncz, B. Völgyesi, L. Hybrid imaging and visualization: Employing machine learning with Mathematica - Python |
| title | Hybrid imaging and visualization: Employing machine learning with Mathematica - Python |
| title_full | Hybrid imaging and visualization: Employing machine learning with Mathematica - Python |
| title_fullStr | Hybrid imaging and visualization: Employing machine learning with Mathematica - Python |
| title_full_unstemmed | Hybrid imaging and visualization: Employing machine learning with Mathematica - Python |
| title_short | Hybrid imaging and visualization: Employing machine learning with Mathematica - Python |
| title_sort | hybrid imaging and visualization: employing machine learning with mathematica - python |
| url | http://hdl.handle.net/20.500.11937/86494 |