Deep ConvLSTM With Self-Attention for Human Activity Decoding Using Wearable Sensors-Reference-Cited by-同舟云学术

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Deep ConvLSTM With Self-Attention for Human Activity Decoding Using Wearable Sensors

Published:2021-03-15 Issue:6 Volume:21 Page:8575-8582
ISSN:1530-437X
Container-title:IEEE Sensors Journal
language:
Short-container-title:IEEE Sensors J.

Author:

Singh Satya P.¹^ORCID,Sharma Madan Kumar²^ORCID,Lay-Ekuakille Aime³^ORCID,Gangwar Deepak⁴^ORCID,Gupta Sukrit¹^ORCID

Affiliation:

1. School of Computer Science and Engineering (SCSE), Nanyang Technological University, Singapore

2. Department of Electronics and Communication Engineering (ECE), Galgotias College of Engineering and Technology, Greater Noida, India

3. Department of Innovation Engineering, University of Salento, Lecce, Italy

4. Department of Electronics and Communication Engineering, Bharati Vidhyapeeth’s College of Engineering, New Delhi, India

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Instrumentation

Link

http://xplorestaging.ieee.org/ielx7/7361/9357819/09296308.pdf?arnumber=9296308

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1. Smart-watch-based construction worker activity recognition with hand-held power tools;Automation in Construction;2024-11

2. IMUGPT 2.0: Language-Based Cross Modality Transfer for Sensor-Based Human Activity Recognition;Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies;2024-08-22

3. A robust multimodal detection system: physical exercise monitoring in long-term care environments;Frontiers in Bioengineering and Biotechnology;2024-08-08

4. RepMobile: A MobileNet-Like Network With Structural Reparameterization for Sensor-Based Human Activity Recognition;IEEE Sensors Journal;2024-08-01

5. A Dual Pipeline With Spatio-Temporal Attention Fusion Approach for Human Activity Recognition;IEEE Sensors Journal;2024-08-01

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