RecurrentHAR: A Novel Transfer Learning-Based Deep Learning Model for Sequential, Complex, Concurrent, Interleaved, and Heterogeneous Type Human Activity Recognition-Reference-Cited by-同舟云学术

RecurrentHAR: A Novel Transfer Learning-Based Deep Learning Model for Sequential, Complex, Concurrent, Interleaved, and Heterogeneous Type Human Activity Recognition

Published:2022-07-26 Issue: Volume: Page:1-22
ISSN:0256-4602
Container-title:IETE Technical Review
language:en
Short-container-title:IETE Technical Review

Author:

Kumar Prabhat¹^ORCID,Suresh S.¹^ORCID

Affiliation:

1. Department of Computer Science, Institute of Science, Banaras Hindu University, Varanasi, 221 005, India.

Publisher

Informa UK Limited

Subject

Electrical and Electronic Engineering

Link

https://www.tandfonline.com/doi/pdf/10.1080/02564602.2022.2101557

Reference69 articles.

1. Deep learning for sensor-based activity recognition: A survey

2. A review of multimodal human activity recognition with special emphasis on classification, applications, challenges and future directions

3. Body Temperature—Indoor Condition Monitor and Activity Recognition by MEMS Accelerometer Based on IoT-Alert System for People in Quarantine Due to COVID-19

4. LSTM Networks Using Smartphone Data for Sensor-Based Human Activity Recognition in Smart Homes

5. Towards Detecting Biceps Muscle Fatigue in Gym Activity Using Wearables

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