Isbn: 9781032635132 - deep learning in biomedical signal and medical imaging (artificial intelligence for sustainable engineering and management) (8 resultados)

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  • Idioma: Inglés

    Editorial: Taylor and Francis Ltd, 2026

    1032635134 / 9781032635132

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    Librería: PBShop.store UK, Fairford, GLOS, Reino UnidoPBShop.store UK

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    PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.

  • Idioma: Inglés

    Editorial: Taylor and Francis Ltd, 2026

    1032635134 / 9781032635132

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    Librería: PBShop.store US, Wood Dale, IL, Estados Unidos de AmericaPBShop.store US

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    PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.

  • Idioma: Inglés

    Editorial: Taylor & Francis Ltd, 2026

    1032635134 / 9781032635132

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    Librería: Revaluation Books, Exeter, Reino UnidoRevaluation Books

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    EUR 115,24

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    Paperback. Condición: Brand New. 256 pages. 6.14x0.62x9.21 inches. In Stock.

  • Idioma: Inglés

    Editorial: CRC Press, 2026

    1032635134 / 9781032635132

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    Librería: moluna, Greven, Alemaniamoluna

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    EUR 86,67

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    Condición: New. Ngangbam Herojit Singh is presently working as an Assistant Professor at NIT Agartala in the Department of Computer Science and Engineering. He received his Ph.D. degree from the NIT Manipur, and M.Tech and B.Tech from Anna University, Chennai. Hi.

  • Idioma: Inglés

    Editorial: Taylor & Francis Ltd (Sales) Jul 2026, 2026

    1032635134 / 9781032635132

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    Librería: AHA-BUCH GmbH, Einbeck, AlemaniaAHA-BUCH GmbH

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    EUR 117,39

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    Taschenbuch. Condición: Neu. Neuware - This book offers detailed information on biomedical imaging using Deep Convolutional Neural Networks (Deep CNN). It focuses on different types of biomedical images to enable readers to understand the effectiveness and the potential. It includes topics such as disease diagnosis and image processing perspectives.Deep Learning in Biomedical Signal and Medical Imaging discusses classification, segmentation, detection, tracking, and retrieval applications of non-invasive methods such as EEG, ECG, EMG, MRI, fMRI, CT, and X-RAY, amongst others. It surveys the most recent techniques and approaches in this field, with both broad coverage and enough depth to be of practical use to working professionals. It includes examples of the application of signal and image processing employing Deep CNN to Alzheimer's, brain tumor, skin cancer, breast cancer, and stroke prediction, as well as ECG and EEG signals. This book offers enough fundamental and technical information on these techniques, approaches, and related problems without overcrowding the reader's head. It presents the results of the latest investigations in the field of Deep CNN for biomedical data analysis. The techniques and approaches presented in this book deal with the most important and/or the newest topics encountered in this field. They combine the fundamental theory of artificial intelligence (AI), machine learning (ML,) and Deep CNN with practical applications in biology and medicine. Certainly, the list of topics covered in this book is not exhaustive, but these topics will shed light on the implications of the presented techniques and approaches on other topics in biomedical data analysis.The book is written for graduate students, researchers, and professionals in biomedical engineering, electrical engineering, signal process engineering, biomedical imaging, and computer science. The specific and innovative solutions covered in this book for both medical and biomedical applications are critical to scientists, researchers, practitioners, professionals, and educators who are working in the context of the topics.…

  • Idioma: Inglés

    Editorial: Taylor & Francis Ltd, London, 2026

    1032635134 / 9781032635132

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    Librería: Grand Eagle Retail, Bensenville, IL, Estados Unidos de AmericaGrand Eagle Retail

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    EUR 62,45

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    Cantidad disponible: 1 disponible

    Paperback. Condición: new. Paperback. This book offers detailed information on biomedical imaging using Deep Convolutional Neural Networks (Deep CNN). It focuses on different types of biomedical images to enable readers to understand the effectiveness and the potential. It includes topics such as disease diagnosis and image processing perspectives.Deep Learning in Biomedical Signal and Medical Imaging discusses classification, segmentation, detection, tracking, and retrieval applications of non-invasive methods such as EEG, ECG, EMG, MRI, fMRI, CT, and X-RAY, amongst others. It surveys the most recent techniques and approaches in this field, with both broad coverage and enough depth to be of practical use to working professionals. It includes examples of the application of signal and image processing employing Deep CNN to Alzheimers, brain tumor, skin cancer, breast cancer, and stroke prediction, as well as ECG and EEG signals. This book offers enough fundamental and technical information on these techniques, approaches, and related problems without overcrowding the readers head. It presents the results of the latest investigations in the field of Deep CNN for biomedical data analysis. The techniques and approaches presented in this book deal with the most important and/or the newest topics encountered in this field. They combine the fundamental theory of artificial intelligence (AI), machine learning (ML,) and Deep CNN with practical applications in biology and medicine. Certainly, the list of topics covered in this book is not exhaustive, but these topics will shed light on the implications of the presented techniques and approaches on other topics in biomedical data analysis.The book is written for graduate students, researchers, and professionals in biomedical engineering, electrical engineering, signal process engineering, biomedical imaging, and computer science. The specific and innovative solutions covered in this book for both medical and biomedical applications are critical to scientists, researchers, practitioners, professionals, and educators who are working in the context of the topics. This book offers detailed information on biomedical imaging using Deep Convolutional Neural Networks (Deep CNN). It focuses on different types of biomedical images to enable readers to understand the effectiveness and the potential. It includes topics such as disease diagnosis, and image processing perspectives. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

  • Idioma: Inglés

    Editorial: Taylor & Francis Ltd, London, 2026

    1032635134 / 9781032635132

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    Librería: CitiRetail, Stevenage, Reino UnidoCitiRetail

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    EUR 63,43

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    Cantidad disponible: 1 disponible

    Paperback. Condición: new. Paperback. This book offers detailed information on biomedical imaging using Deep Convolutional Neural Networks (Deep CNN). It focuses on different types of biomedical images to enable readers to understand the effectiveness and the potential. It includes topics such as disease diagnosis and image processing perspectives.Deep Learning in Biomedical Signal and Medical Imaging discusses classification, segmentation, detection, tracking, and retrieval applications of non-invasive methods such as EEG, ECG, EMG, MRI, fMRI, CT, and X-RAY, amongst others. It surveys the most recent techniques and approaches in this field, with both broad coverage and enough depth to be of practical use to working professionals. It includes examples of the application of signal and image processing employing Deep CNN to Alzheimers, brain tumor, skin cancer, breast cancer, and stroke prediction, as well as ECG and EEG signals. This book offers enough fundamental and technical information on these techniques, approaches, and related problems without overcrowding the readers head. It presents the results of the latest investigations in the field of Deep CNN for biomedical data analysis. The techniques and approaches presented in this book deal with the most important and/or the newest topics encountered in this field. They combine the fundamental theory of artificial intelligence (AI), machine learning (ML,) and Deep CNN with practical applications in biology and medicine. Certainly, the list of topics covered in this book is not exhaustive, but these topics will shed light on the implications of the presented techniques and approaches on other topics in biomedical data analysis.The book is written for graduate students, researchers, and professionals in biomedical engineering, electrical engineering, signal process engineering, biomedical imaging, and computer science. The specific and innovative solutions covered in this book for both medical and biomedical applications are critical to scientists, researchers, practitioners, professionals, and educators who are working in the context of the topics. This book offers detailed information on biomedical imaging using Deep Convolutional Neural Networks (Deep CNN). It focuses on different types of biomedical images to enable readers to understand the effectiveness and the potential. It includes topics such as disease diagnosis, and image processing perspectives. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

  • Idioma: Inglés

    Editorial: Taylor & Francis Ltd, London, 2026

    1032635134 / 9781032635132

    • Tapa blanda
    • Impresión bajo demanda

    Librería: AussieBookSeller, Truganina, VIC, AustraliaAussieBookSeller

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    Condición: Nuevo

    EUR 116,10

    Envío por EUR 32,89 
    Se envía de Australia a Estados Unidos de America

    Cantidad disponible: 1 disponible

    Paperback. Condición: new. Paperback. This book offers detailed information on biomedical imaging using Deep Convolutional Neural Networks (Deep CNN). It focuses on different types of biomedical images to enable readers to understand the effectiveness and the potential. It includes topics such as disease diagnosis and image processing perspectives.Deep Learning in Biomedical Signal and Medical Imaging discusses classification, segmentation, detection, tracking, and retrieval applications of non-invasive methods such as EEG, ECG, EMG, MRI, fMRI, CT, and X-RAY, amongst others. It surveys the most recent techniques and approaches in this field, with both broad coverage and enough depth to be of practical use to working professionals. It includes examples of the application of signal and image processing employing Deep CNN to Alzheimers, brain tumor, skin cancer, breast cancer, and stroke prediction, as well as ECG and EEG signals. This book offers enough fundamental and technical information on these techniques, approaches, and related problems without overcrowding the readers head. It presents the results of the latest investigations in the field of Deep CNN for biomedical data analysis. The techniques and approaches presented in this book deal with the most important and/or the newest topics encountered in this field. They combine the fundamental theory of artificial intelligence (AI), machine learning (ML,) and Deep CNN with practical applications in biology and medicine. Certainly, the list of topics covered in this book is not exhaustive, but these topics will shed light on the implications of the presented techniques and approaches on other topics in biomedical data analysis.The book is written for graduate students, researchers, and professionals in biomedical engineering, electrical engineering, signal process engineering, biomedical imaging, and computer science. The specific and innovative solutions covered in this book for both medical and biomedical applications are critical to scientists, researchers, practitioners, professionals, and educators who are working in the context of the topics. This book offers detailed information on biomedical imaging using Deep Convolutional Neural Networks (Deep CNN). It focuses on different types of biomedical images to enable readers to understand the effectiveness and the potential. It includes topics such as disease diagnosis, and image processing perspectives. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.…