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Da: GreatBookPricesUK, Woodford Green, Regno Unito
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Da: Majestic Books, Hounslow, Regno Unito
EUR 134,16
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Da: GreatBookPricesUK, Woodford Green, Regno Unito
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Aggiungi al carrelloHardback. Condizione: New. New copy - Usually dispatched within 4 working days.
Da: Ria Christie Collections, Uxbridge, Regno Unito
EUR 149,64
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Da: Biblios, Frankfurt am main, HESSE, Germania
EUR 156,00
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Aggiungi al carrelloCondizione: New.
Lingua: Inglese
Editore: TAYLOR & FRANCIS NP EXCLUSIVE(CBS), 2026
ISBN 10: 1032753242 ISBN 13: 9781032753249
Da: UK BOOKS STORE, London, LONDO, Regno Unito
EUR 191,22
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Aggiungi al carrelloCondizione: New. Brand New ! Fast Delivery "International Edition " and ship within 24-48 hours. Deliver by FedEx and Dhl, & Aramex, UPS, & USPS and we do accept APO and PO BOX Addresses. Order can be delivered worldwide within 4-6 Working days .and we do have flat rate for up to 2LB. Extra shipping charges will be requested This Item May be shipped from India, United states & United Kingdom. Depending on your location and availability.
Da: Revaluation Books, Exeter, Regno Unito
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Aggiungi al carrelloHardcover. Condizione: Brand New. 208 pages. 9.18x6.12x9.21 inches. In Stock.
Lingua: Inglese
Editore: Taylor & Francis Np Exclusive(Cbs),, 2026
Da: Books in my Basket, New Delhi, India
EUR 155,20
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Aggiungi al carrelloN.A. Condizione: New. ISBN:9781032753249.
Lingua: Inglese
Editore: Taylor & Francis Ltd, London, 2025
ISBN 10: 1032753242 ISBN 13: 9781032753249
Da: Grand Eagle Retail, Bensenville, IL, U.S.A.
Hardcover. Condizione: new. Hardcover. This book presents various machine learning applications in the field of engineering with a focus on deep learning-based machine learning approaches. It examines the relationship between three different multidisciplinary engineering branches: biomedical engineering, signal processing, and computer science.Applied Artificial Intelligence and Machine Learning Techniques for Engineering Applications explores recent advancements in the use of AI/ML in practical engineering applications by inviting top experts to share the outcomes of their most recent work. Among the topics explored are detection, measurement, and monitoring of signals (biosensors and biomedical devices) and the use of diagnostic interpretations of bioelectric data using signal-processing techniques. The authors also address several machine learning tasks, such as classification (supervised learning) and clustering (unsupervised learning), in the context of engineering. Finally, the book also describes the development of new biomaterials for use in the body.The book will be a great help to researchers and academics working in the fields of biomedical signaling and/or human-machine interface. This book presents machine learning applications in the field of engineering with a focus on deep learning-based machine learning approaches. It examines the relationship between three different multidisciplinary engineering branches: Biomedical Engineering, Signal Processing, and Computer Science. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Lingua: Inglese
Editore: Taylor & Francis Ltd, London, 2025
ISBN 10: 1032753242 ISBN 13: 9781032753249
Da: CitiRetail, Stevenage, Regno Unito
EUR 110,11
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Aggiungi al carrelloHardcover. Condizione: new. Hardcover. This book presents various machine learning applications in the field of engineering with a focus on deep learning-based machine learning approaches. It examines the relationship between three different multidisciplinary engineering branches: biomedical engineering, signal processing, and computer science.Applied Artificial Intelligence and Machine Learning Techniques for Engineering Applications explores recent advancements in the use of AI/ML in practical engineering applications by inviting top experts to share the outcomes of their most recent work. Among the topics explored are detection, measurement, and monitoring of signals (biosensors and biomedical devices) and the use of diagnostic interpretations of bioelectric data using signal-processing techniques. The authors also address several machine learning tasks, such as classification (supervised learning) and clustering (unsupervised learning), in the context of engineering. Finally, the book also describes the development of new biomaterials for use in the body.The book will be a great help to researchers and academics working in the fields of biomedical signaling and/or human-machine interface. This book presents machine learning applications in the field of engineering with a focus on deep learning-based machine learning approaches. It examines the relationship between three different multidisciplinary engineering branches: Biomedical Engineering, Signal Processing, and Computer Science. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
Da: PBShop.store UK, Fairford, GLOS, Regno Unito
EUR 152,16
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Aggiungi al carrelloHRD. Condizione: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
Da: PBShop.store US, Wood Dale, IL, U.S.A.
EUR 157,65
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Aggiungi al carrelloHRD. Condizione: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
Da: THE SAINT BOOKSTORE, Southport, Regno Unito
EUR 165,07
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Aggiungi al carrelloHardback. Condizione: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days 526.
Da: moluna, Greven, Germania
EUR 158,56
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Aggiungi al carrelloCondizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Dr. Ravichander Janapati is presently working as an Associate Professor at Department of ECE, SR University, Warangal, Telangana, India. He is a senior member of IEEE, and he graduated in Electronics and Communication Engineering from JNTU Hyderab.
Lingua: Inglese
Editore: Taylor & Francis Ltd, London, 2025
ISBN 10: 1032753242 ISBN 13: 9781032753249
Da: AussieBookSeller, Truganina, VIC, Australia
EUR 223,97
Quantità: 1 disponibili
Aggiungi al carrelloHardcover. Condizione: new. Hardcover. This book presents various machine learning applications in the field of engineering with a focus on deep learning-based machine learning approaches. It examines the relationship between three different multidisciplinary engineering branches: biomedical engineering, signal processing, and computer science.Applied Artificial Intelligence and Machine Learning Techniques for Engineering Applications explores recent advancements in the use of AI/ML in practical engineering applications by inviting top experts to share the outcomes of their most recent work. Among the topics explored are detection, measurement, and monitoring of signals (biosensors and biomedical devices) and the use of diagnostic interpretations of bioelectric data using signal-processing techniques. The authors also address several machine learning tasks, such as classification (supervised learning) and clustering (unsupervised learning), in the context of engineering. Finally, the book also describes the development of new biomaterials for use in the body.The book will be a great help to researchers and academics working in the fields of biomedical signaling and/or human-machine interface. This book presents machine learning applications in the field of engineering with a focus on deep learning-based machine learning approaches. It examines the relationship between three different multidisciplinary engineering branches: Biomedical Engineering, Signal Processing, and Computer Science. 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.
Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 206,25
Quantità: 1 disponibili
Aggiungi al carrelloBuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book presents machine learning applications in the field of engineering with a focus on deep learning-based machine learning approaches. It examines the relationship between three different multidisciplinary engineering branches: Biomedical Engineering, Signal Processing, and Computer Science.