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Deep Learning for Human Activity Recognition : Second International Workshop, Dl-har 2020, Held in Conjunction With Ijcai-pricai 2020, Kyoto, Japan, January 8, 2021, Proceedings
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Human Activity Recognition using Wearable Sensors: An Introduction into how Deep Learning can aid Healthcare
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Deep Learning for Human Activity Recognition: Second International Workshop, DL-HAR 2020, Held in Conjunction with IJCAI-PRICAI 2020, Kyoto, Japan, ... in Computer and Information Science)
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Deep Learning for Human Activity Recognition : Second International Workshop, DL-HAR 2020, Held in Conjunction with IJCAI-PRICAI 2020, Kyoto, Japan, J
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Deep Learning for Human Activity Recognition : Second International Workshop, Dl-har 2020, Held in Conjunction With Ijcai-pricai 2020, Kyoto, Japan, January 8, 2021, Proceedings
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Deep Learning For Human Activity Recogni
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Deep Learning for Human Activity Recognition : Second International Workshop, Dl-har 2020, Held in Conjunction With Ijcai-pricai 2020, Kyoto, Japan, January 8, 2021, Proceedings
Anbieter: GreatBookPricesUK, Woodford Green, Vereinigtes Königreich
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Human Activity Recognition using Wearable Sensors: An Introduction into how Deep Learning can aid Healthcare
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Deep Learning for Human Activity Recognition: Second International Workshop, Dl-har 2020, Held in Conjunction With Ijcai-pricai 2020, Kyoto, Japan, January 8, 2021, Proceedings
Sprache: Englisch
Verlag: Springer-Nature New York Inc, 2021
ISBN 10: 9811605742 ISBN 13: 9789811605741
Anbieter: Revaluation Books, Exeter, Vereinigtes Königreich
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In den WarenkorbPaperback. Zustand: Brand New. 151 pages. 9.25x6.10x0.43 inches. In Stock.
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Deep Learning for Human Activity Recognition : Second International Workshop, Dl-har 2020, Held in Conjunction With Ijcai-pricai 2020, Kyoto, Japan, January 8, 2021, Proceedings
Anbieter: GreatBookPrices, Columbia, MD, USA
Verkäuferbewertung 5 von 5 Sternen
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HUMAN ACTIVITY RECOGNITION USING DEEP LEARNING
Sprache: Englisch
Verlag: LAP LAMBERT Academic Publishing, 2023
ISBN 10: 6206767442 ISBN 13: 9786206767442
Zustand: New.
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Deep Learning For Human Activity Recogni
Anbieter: Kennys Bookstore, Olney, MD, USA
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Human Activity Recognition using Wearable Sensors: An Introduction into how Deep Learning can aid Healthcare
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EUR 92,88
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EUR 62,88
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Human Activity Recognition using Wearable Sensors: An Introduction into how Deep Learning can aid Healthcare
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EUR 114,96
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Deep Learning for Human Activity Recognition : Second International Workshop, DL-HAR 2020, Held in Conjunction with IJCAI-PRICAI 2020, Kyoto, Japan, January 8, 2021, Proceedings
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Verkäuferbewertung 5 von 5 Sternen
Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book constitutes refereed proceedings of theSecond International Workshop on Deep Learning for Human Activity Recognition, DL-HAR 2020, held in conjunction with IJCAI-PRICAI 2020, in Kyoto, Japan, in January 2021. Due to the COVID-19 pandemic the workshop was postponed to the year 2021 and held in a virtual format.The 10 presented papers were thorougly reviewed and included in the volume. They present recent research on applications of human activity recognition for various areas such as healthcare services, smart home applications, and more.
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Taschenbuch. Zustand: Neu. Deep Learning for Human Activity Recognition | Second International Workshop, DL-HAR 2020, Held in Conjunction with IJCAI-PRICAI 2020, Kyoto, Japan, January 8, 2021, Proceedings | Xiaoli Li (u. a.) | Taschenbuch | xii | Englisch | 2021 | Springer | EAN 9789811605741 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
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HUMAN ACTIVITY RECOGNITION USING DEEP LEARNING
Sprache: Englisch
Verlag: LAP LAMBERT Academic Publishing, 2023
ISBN 10: 6206767442 ISBN 13: 9786206767442
Taschenbuch. Zustand: Neu. HUMAN ACTIVITY RECOGNITION USING DEEP LEARNING | Tuhin Kumar Bera (u. a.) | Taschenbuch | Englisch | 2023 | LAP LAMBERT Academic Publishing | EAN 9786206767442 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.
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Deep Learning for Human Activity Recognition : Second International Workshop, DL-HAR 2020, Held in Conjunction with IJCAI-PRICAI 2020, Kyoto, Japan, January 8, 2021, Proceedings
Sprache: Englisch
Verlag: Springer Nature Singapore, 2021
ISBN 10: 9811605742 ISBN 13: 9789811605741
Zustand: Hervorragend. Zustand: Hervorragend | Sprache: Englisch | Produktart: Bücher | This book constitutes refereed proceedings of the Second International Workshop on Deep Learning for Human Activity Recognition, DL-HAR 2020, held in conjunction with IJCAI-PRICAI 2020, in Kyoto, Japan, in January 2021. Due to the COVID-19 pandemic the workshop was postponed to the year 2021 and held in a virtual format. The 10 presented papers were thorougly reviewed and included in the volume. They present recent research on applications of human activity recognition for various areas such as healthcare services, smart home applications, and more.
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Machine Learning and Deep Learning in Human Activity Recognition and Fall Detection: Algorithms, Frameworks and Applications for Sustainable Healthcare
Anbieter: Revaluation Books, Exeter, Vereinigtes Königreich
Verkäuferbewertung 5 von 5 Sternen
EUR 143,12
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In den WarenkorbHardcover. Zustand: Brand New. 150 pages. 9.25x6.10x9.49 inches. In Stock.
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Machine Learning and Deep Learning in Human Activity Recognition and Fall Detection (Hardcover)
Sprache: Englisch
Verlag: Springer Nature Switzerland AG, Cham, 2026
ISBN 10: 303209240X ISBN 13: 9783032092403
Anbieter: Grand Eagle Retail, Bensenville, IL, USA
Verkäuferbewertung 5 von 5 Sternen
Hardcover. Zustand: new. Hardcover. This book presents research into the domain of Human Activity Recognition (HAR) and Fall Detection (FD), with a focus on the seamless monitoring and support of elderly people. The author shows how current HAR and FD technologies have application in disease monitoring, prediction and identification, as well real-time facilitating early diagnosis of symptom-based disease identification, prediction, and detection. The author discusses existing infrastructure that supports this ecosystem, comprising smartphones, WiFi, 3G/4G Internet connectivity, and low-cost wearable sensors for sustainable health monitoring and care. The book presents smart technologies such as machine learning, deep learning, and Internet of Things that are applied for sensor data analysis and knowledge extraction towards accurate identification of activities and fall events with pre-fall postures in real time. The author also shows how smart and seamless health monitoring and care ecosystem fits with traditional healthcare system for sustainable solutions.Presents smart technologies for sustainable health monitoring and care targeted for the elderly;Discusses techniques for privacy surrounding Human Activity Recognition (HAR) and Fall Detection (FD);Includes case studies, scenario-based studies, sponsored projects, prototypes and successful applications. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Machine Learning and Deep Learning in Human Activity Recognition and Fall Detection (Hardcover)
Sprache: Englisch
Verlag: Springer Nature Switzerland AG, Cham, 2026
ISBN 10: 303209240X ISBN 13: 9783032092403
Anbieter: CitiRetail, Stevenage, Vereinigtes Königreich
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EUR 134,16
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In den WarenkorbHardcover. Zustand: new. Hardcover. This book presents research into the domain of Human Activity Recognition (HAR) and Fall Detection (FD), with a focus on the seamless monitoring and support of elderly people. The author shows how current HAR and FD technologies have application in disease monitoring, prediction and identification, as well real-time facilitating early diagnosis of symptom-based disease identification, prediction, and detection. The author discusses existing infrastructure that supports this ecosystem, comprising smartphones, WiFi, 3G/4G Internet connectivity, and low-cost wearable sensors for sustainable health monitoring and care. The book presents smart technologies such as machine learning, deep learning, and Internet of Things that are applied for sensor data analysis and knowledge extraction towards accurate identification of activities and fall events with pre-fall postures in real time. The author also shows how smart and seamless health monitoring and care ecosystem fits with traditional healthcare system for sustainable solutions.Presents smart technologies for sustainable health monitoring and care targeted for the elderly;Discusses techniques for privacy surrounding Human Activity Recognition (HAR) and Fall Detection (FD);Includes case studies, scenario-based studies, sponsored projects, prototypes and successful applications. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
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Machine Learning and Deep Learning in Human Activity Recognition and Fall Detection : Algorithms, Frameworks, and Applications for Sustainable Healthcare
Sprache: Englisch
Verlag: Springer, Springer International Publishing, 2026
ISBN 10: 303209240X ISBN 13: 9783032092403
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Verkäuferbewertung 5 von 5 Sternen
Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book presents research into the domain of Human Activity Recognition (HAR) and Fall Detection (FD), with a focus on the seamless monitoring and support of elderly people. The author shows how current HAR and FD technologies have application in disease monitoring, prediction and identification, as well real-time facilitating early diagnosis of symptom-based disease identification, prediction, and detection. The author discusses existing infrastructure that supports this ecosystem, comprising smartphones, WiFi, 3G/4G Internet connectivity, and low-cost wearable sensors for sustainable health monitoring and care. The book presents smart technologies such as machine learning, deep learning, and Internet of Things that are applied for sensor data analysis and knowledge extraction towards accurate identification of activities and fall events with pre-fall postures in real time. The author also shows how smart and seamless health monitoring and care ecosystem fits with traditional healthcare system for sustainable solutions.Presents smart technologies for sustainable health monitoring and care targeted for the elderly;Discusses techniques for privacy surrounding Human Activity Recognition (HAR) and Fall Detection (FD);Includes case studies, scenario-based studies, sponsored projects, prototypes and successful applications.
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Machine Learning and Deep Learning in Human Activity Recognition and Fall Detection: Algorithms, Frameworks and Applications for Sustainable Healthcare
Anbieter: Revaluation Books, Exeter, Vereinigtes Königreich
Verkäuferbewertung 5 von 5 Sternen
EUR 219,88
EUR 11,58 Versand
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In den WarenkorbHardcover. Zustand: Brand New. 150 pages. 9.25x6.10x9.49 inches. In Stock.
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Machine Learning and Deep Learning in Human Activity Recognition and Fall Detection (Hardcover)
Sprache: Englisch
Verlag: Springer Nature Switzerland AG, Cham, 2026
ISBN 10: 303209240X ISBN 13: 9783032092403
Anbieter: AussieBookSeller, Truganina, VIC, Australien
Verkäuferbewertung 5 von 5 Sternen
Hardcover. Zustand: new. Hardcover. This book presents research into the domain of Human Activity Recognition (HAR) and Fall Detection (FD), with a focus on the seamless monitoring and support of elderly people. The author shows how current HAR and FD technologies have application in disease monitoring, prediction and identification, as well real-time facilitating early diagnosis of symptom-based disease identification, prediction, and detection. The author discusses existing infrastructure that supports this ecosystem, comprising smartphones, WiFi, 3G/4G Internet connectivity, and low-cost wearable sensors for sustainable health monitoring and care. The book presents smart technologies such as machine learning, deep learning, and Internet of Things that are applied for sensor data analysis and knowledge extraction towards accurate identification of activities and fall events with pre-fall postures in real time. The author also shows how smart and seamless health monitoring and care ecosystem fits with traditional healthcare system for sustainable solutions.Presents smart technologies for sustainable health monitoring and care targeted for the elderly;Discusses techniques for privacy surrounding Human Activity Recognition (HAR) and Fall Detection (FD);Includes case studies, scenario-based studies, sponsored projects, prototypes and successful applications. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
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Deep Learning for Human Activity Recognition (eng)
Anbieter: Brook Bookstore On Demand, Napoli, NA, Italien
Verkäuferbewertung 4 von 5 Sternen
EUR 46,22
EUR 5,50 Versand
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In den WarenkorbZustand: new. Questo è un articolo print on demand.
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Deep Learning for Human Activity Recognition: Second International Workshop, DL-HAR 2020, Held in Conjunction with IJCAI-PRICAI 2020, Kyoto, Japan, . in Computer and Information Science, 1370) 1st ed. 2021 Edition
Anbieter: Majestic Books, Hounslow, Vereinigtes Königreich
Verkäuferbewertung 4 von 5 Sternen
EUR 69,22
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Deep Learning for Human Activity Recognition
Sprache: Englisch
Verlag: Springer Nature Singapore Feb 2021, 2021
ISBN 10: 9811605742 ISBN 13: 9789811605741
Anbieter: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Deutschland
Verkäuferbewertung 5 von 5 Sternen
Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book constitutes refereed proceedings of theSecond International Workshop on Deep Learning for Human Activity Recognition, DL-HAR 2020, held in conjunction with IJCAI-PRICAI 2020, in Kyoto, Japan, in January 2021. Due to the COVID-19 pandemic the workshop was postponed to the year 2021 and held in a virtual format.The 10 presented papers were thorougly reviewed and included in the volume. They present recent research on applications of human activity recognition for various areas such as healthcare services, smart home applications, and more. 152 pp. Englisch.
