Deep Learning Human Activity (47 results)
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
Li, Xiaoli (EDT); Wu, Min (EDT); Chen, Zhenghua (EDT); Zhang, Le (EDT)
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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
Li, Xiaoli (EDT); Wu, Min (EDT); Chen, Zhenghua (EDT); Zhang, Le (EDT)
- Softcover
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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
Li, Xiaoli (EDT); Wu, Min (EDT); Chen, Zhenghua (EDT); Zhang, Le (EDT)
- Softcover
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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
Li, Xiaoli (EDT); Wu, Min (EDT); Chen, Zhenghua (EDT); Zhang, Le (EDT)
- Softcover
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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
Li, Xiaoli (Editor)/ Wu, Min (Editor)/ Chen, Zhenghua (Editor)/ Zhang, Le (Editor)
- Softcover
Seller: Revaluation Books, Exeter, United KingdomRevaluation Books
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Taschenbuch. Condition: 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. Condition: 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 E…U: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
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Taschenbuch. Condition: 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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Condition: 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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Hardcover. Condition: 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 identifi…cation, 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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Hardcover. Condition: 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 identifi…cation, 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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Buch. Condition: 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 diseas…e 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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Hardcover. Condition: 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 identifi…cation, 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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Taschenbuch. Condition: 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 CO…VID-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.
