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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 / edited by Xiaoli Li, Min Wu, Zhenghua Chen, Le Zhang.
- Format:
- Book
- Series:
- Computer Science (SpringerNature-11645)
- Communications in computer and information science 1865-0937 ; 1370
- Communications in Computer and Information Science, 1865-0937 ; 1370
- Language:
- English
- Subjects (All):
- Artificial intelligence.
- Pattern recognition systems.
- User interfaces (Computer systems).
- Human-computer interaction.
- Computer vision.
- Application software.
- Computers, Special purpose.
- Artificial Intelligence.
- Automated Pattern Recognition.
- User Interfaces and Human Computer Interaction.
- Computer Vision.
- Computer and Information Systems Applications.
- Special Purpose and Application-Based Systems.
- Local Subjects:
- Artificial Intelligence.
- Automated Pattern Recognition.
- User Interfaces and Human Computer Interaction.
- Computer Vision.
- Computer and Information Systems Applications.
- Special Purpose and Application-Based Systems.
- Physical Description:
- 1 online resource (XII, 139 pages) : 51 illustrations, 49 illustrations in color.
- Edition:
- 1st ed. 2021.
- Contained In:
- Springer Nature eBook
- Place of Publication:
- Singapore : Springer Nature Singapore : Imprint: Springer, 2021.
- System Details:
- text file PDF
- Summary:
- 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. .
- Contents:
- 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.
- Other Format:
- Printed edition:
- ISBN:
- 978-981-16-0575-8
- 9789811605758
- Access Restriction:
- Restricted for use by site license.
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