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Deep learning for human activity rec...

International Workshop on Deep Learning for Human Activity Recognition (2020 :)

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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 /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Deep learning for human activity recognition/ edited by Xiaoli Li ... [et al.].
其他題名:	second International Workshop, DL-HAR 2020, held in conjunction with IJCAI-PRICAI 2020, Kyoto, Japan, January 8, 2021 : proceedings /
其他題名:	DL-HAR 2020
其他作者:	Li, Xiaoli.
團體作者:	International Workshop on Deep Learning for Human Activity Recognition
出版者:	Singapore :Springer Singapore : : 2021.,
面頁冊數:	xii, 139 p. :ill. (some col.), digital ;24 cm.
內容註:	Human Activity Recognition using Wearable Sensors: Review, Challenges, Evaluation Benchmark -- Wheelchair Behavior Recognition for Visualizing Sidewalk Accessibility by Deep Neural Networks -- Toward Data Augmentation and Interpretation in Sensor-Based Fine-Grained Hand Activity Recognition -- Personalization Models for Human Activity Recognition With Distribution Matching-Based Metrics -- Resource-Constrained Federated Learning with Heterogeneous Labels and Models for Human Activity Recognition -- ARID: A New Dataset for Recognizing Action in the Dark -- Single Run Action Detector over Video Stream - A Privacy Preserving Approach -- Efﬁcacy of Model Fine-Tuning for Personalized Dynamic Gesture Recognition -- Fully Convolutional Network Bootstrapped by Word Encoding and Embedding for Activity Recognition in Smart Homes -- Towards User Friendly Medication Mapping Using Entity-Boosted Two-Tower Neural Network.
Contained By:	Springer Nature eBook
標題:	Human activity recognition - Congresses. -
電子資源:	https://doi.org/10.1007/978-981-16-0575-8
ISBN:	9789811605758

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 /
Deep learning for human activity recognitionsecond International Workshop, DL-HAR 2020, held in conjunction with IJCAI-PRICAI 2020, Kyoto, Japan, January 8, 2021 : proceedings /[electronic resource] :DL-HAR 2020edited by Xiaoli Li ... [et al.]. - Singapore :Springer Singapore :2021. - xii, 139 p. :ill. (some col.), digital ;24 cm. - Communications in computer and information science,v.13701865-0929 ;. - Communications in computer and information science ;v.1370..

Human Activity Recognition using Wearable Sensors: Review, Challenges, Evaluation Benchmark -- Wheelchair Behavior Recognition for Visualizing Sidewalk Accessibility by Deep Neural Networks -- Toward Data Augmentation and Interpretation in Sensor-Based Fine-Grained Hand Activity Recognition -- Personalization Models for Human Activity Recognition With Distribution Matching-Based Metrics -- Resource-Constrained Federated Learning with Heterogeneous Labels and Models for Human Activity Recognition -- ARID: A New Dataset for Recognizing Action in the Dark -- Single Run Action Detector over Video Stream - A Privacy Preserving Approach -- Efﬁcacy of Model Fine-Tuning for Personalized Dynamic Gesture Recognition -- Fully Convolutional Network Bootstrapped by Word Encoding and Embedding for Activity Recognition in Smart Homes -- Towards User Friendly Medication Mapping Using Entity-Boosted Two-Tower Neural Network.

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.

ISBN: 9789811605758

Standard No.: 10.1007/978-981-16-0575-8doiSubjects--Topical Terms:

3488746
Human activity recognition
--Congresses.

LC Class. No.: Q325.5 / .I57 2020

Dewey Class. No.: 006.31

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