Verlag: Taylor & Francis Ltd, London, 2024
ISBN 10: 1032550821 ISBN 13: 9781032550824
Sprache: Englisch
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In den WarenkorbHardcover. Zustand: new. Hardcover. The text begins by highlighting the benefits of the Internet of Things-enabled machine learning in the healthcare sector, examines the diagnosis of diseases using machine learning algorithms, and analyzes security and privacy issues in the healthcare systems using the Internet of Things. The text elaborates on image processing implementation for medical images to detect and classify diseases based on magnetic resonance imaging and ultrasound images.This book:Covers the procedure to recognize emotions using image processing and the Internet of Things-enabled machine learningHighlights security and privacy issues in the healthcare system using the Internet of ThingsDiscusses classification and implementation techniques of image segmentationExplains different algorithms of machine learning for image processing in a comprehensive mannerProvides computational intelligence on the Internet of Things for future biomedical applications including lung cancerIt is primarily written for graduate students and academic researchers in the fields of electrical engineering, electronics and communications engineering, computer science and engineering, and biomedical engineering. The text begins by highlighting the benefits of the internet of things enabled machine learning in the healthcare sector, examines the diagnosis of diseases using machine learning algorithms, and examines security and privacy issues in the healthcare systems using the internet of things. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
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Verlag: Taylor & Francis Ltd, London, 2024
ISBN 10: 1032550821 ISBN 13: 9781032550824
Sprache: Englisch
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In den WarenkorbHardcover. Zustand: new. Hardcover. The text begins by highlighting the benefits of the Internet of Things-enabled machine learning in the healthcare sector, examines the diagnosis of diseases using machine learning algorithms, and analyzes security and privacy issues in the healthcare systems using the Internet of Things. The text elaborates on image processing implementation for medical images to detect and classify diseases based on magnetic resonance imaging and ultrasound images.This book:Covers the procedure to recognize emotions using image processing and the Internet of Things-enabled machine learningHighlights security and privacy issues in the healthcare system using the Internet of ThingsDiscusses classification and implementation techniques of image segmentationExplains different algorithms of machine learning for image processing in a comprehensive mannerProvides computational intelligence on the Internet of Things for future biomedical applications including lung cancerIt is primarily written for graduate students and academic researchers in the fields of electrical engineering, electronics and communications engineering, computer science and engineering, and biomedical engineering. The text begins by highlighting the benefits of the internet of things enabled machine learning in the healthcare sector, examines the diagnosis of diseases using machine learning algorithms, and examines security and privacy issues in the healthcare systems using the internet of things. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Verlag: Taylor & Francis Ltd, London, 2024
ISBN 10: 1032550821 ISBN 13: 9781032550824
Sprache: Englisch
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In den WarenkorbHardcover. Zustand: new. Hardcover. The text begins by highlighting the benefits of the Internet of Things-enabled machine learning in the healthcare sector, examines the diagnosis of diseases using machine learning algorithms, and analyzes security and privacy issues in the healthcare systems using the Internet of Things. The text elaborates on image processing implementation for medical images to detect and classify diseases based on magnetic resonance imaging and ultrasound images.This book: Covers the procedure to recognize emotions using image processing and the Internet of Things-enabled machine learning. Highlights security and privacy issues in the healthcare system using the Internet of Things. Discusses classification and implementation techniques of image segmentation. Explains different algorithms of machine learning for image processing in a comprehensive manner. Provides computational intelligence on the Internet of Things for future biomedical applications including lung cancer.It is primarily written for graduate students and academic researchers in the fields of electrical engineering, electronics and communications engineering, computer science and engineering, and biomedical engineering. The text begins by highlighting the benefits of the internet of things enabled machine learning in the healthcare sector, examines the diagnosis of diseases using machine learning algorithms, and examines security and privacy issues in the healthcare systems using the internet of things. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
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In den WarenkorbHardcover. Zustand: Brand New. 512 pages. 9.19x6.13x9.21 inches. In Stock.
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In den WarenkorbZustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Dr. Neha Goel is working as Professor in the Department of Electronics & Communication Engineering, RKGIT, Ghaziabad, India. She has Ph.D. degree from SRM University, Chennai, in 2019. She has 18 years of rich experience in teaching and research and .
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In den WarenkorbBuch. Zustand: Neu. Internet of Things enabled Machine Learning for Biomedical Applications | Neha Goel (u. a.) | Buch | Einband - fest (Hardcover) | Englisch | 2024 | CRC Press | EAN 9781032550824 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.
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In den WarenkorbBuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The text begins by highlighting the benefits of the internet of things enabled machine learning in the healthcare sector, examines the diagnosis of diseases using machine learning algorithms, and examines security and privacy issues in the healthcare systems using the internet of things.