Multimodality imaging. Volume 1, Deep learning applications /

This research and reference text explores the finer details of deep learning models. It provides a brief outline on popular models including convolution neural networks, deep belief networks, autoencoders and residual neural networks.

Gespeichert in:
Weitere Titel:
Multimodality Imaging
Multimodality Imaging, Volume 1
Hauptverfasser:
Biswas, Mainak, Suri, Jasjit S.
Weitere Verfasser:
Biswas, Mainak (HerausgeberIn), Suri, Jasjit S. (HerausgeberIn)
Format:
Elektronisch E-Book
Sprache:
Englisch
Veröffentlicht:
Bristol [England] (Temple Circus, Temple Way, Bristol BS1 6HG, UK) : IOP Publishing, [2022]
Zusammenfassung:
This research and reference text explores the finer details of deep learning models. It provides a brief outline on popular models including convolution neural networks, deep belief networks, autoencoders and residual neural networks.
Umfang:
1 online resource (various pagings) : illustrations (some color).
Also available in print.
Mode of access: World Wide Web.
System requirements: Adobe Acrobat Reader, EPUB reader, or Kindle reader.
Anmerkungen:
"Version: 20221201"--Title page verso.
Format Details:
Mode of access: World Wide Web.
System requirements: Adobe Acrobat Reader, EPUB reader, or Kindle reader.
Zielpublikum:
Academic and industry researchers in medical imaging analysis, and for graduate students taking courses on machine learning and deep learning for computer vision and medical image computing and analysis.
Bibliografie:
Includes bibliographical references.
ISBN:
0-7503-2244-6
0-7503-2243-8
Schlagworte:
Diagnostic imaging > Data processing.
Deep learning (Machine learning)
Computer vision.
Diagnostic Imaging.
Deep Learning.
Visual Perception.
Biomedical engineering.
TECHNOLOGY & ENGINEERING / Biomedical.
Sistemes d'imatges
Comunicació multimodal
Aprenentatge profund
Llibres electrònics
Bezugswerke:
Links: