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Record Nr. |
UNINA9910366653803321 |
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Autore |
Awange Joseph |
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Titolo |
Hybrid Imaging and Visualization : Employing Machine Learning with Mathematica - Python / / by Joseph Awange, Béla Paláncz, Lajos Völgyesi |
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Pubbl/distr/stampa |
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Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 |
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ISBN |
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Edizione |
[1st ed. 2020.] |
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Descrizione fisica |
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1 online resource (xvii, 406 pages) : illustrations |
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Disciplina |
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Soggetti |
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Remote sensing |
Optical data processing |
Geophysics |
Space sciences |
Remote Sensing/Photogrammetry |
Computer Imaging, Vision, Pattern Recognition and Graphics |
Geophysics/Geodesy |
Space Sciences (including Extraterrestrial Physics, Space Exploration and Astronautics) |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di bibliografia |
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Includes bibliographical references. |
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Nota di contenuto |
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Dimension reduction -- Classification -- Clustering -- Regression -- Neural Networks. |
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Sommario/riassunto |
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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. |
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