IoT-based Human Activity Recognition Models based on CNN, LSTM and GRU-Reference-Cited by-同舟云学术

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IoT-based Human Activity Recognition Models based on CNN, LSTM and GRU

Published:2022-11-04 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE Silchar Subsection Conference (SILCON)
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Author:

Kolkar Ranjit¹,Singh Tomar Rudra Pratap¹,Vasantha Geetha¹

Affiliation:

1. National Institute of Technology Karnataka,Department of Information Technology,Surathkal,Manglore,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10028779/10028780/10028803.pdf?arnumber=10028803

Reference29 articles.

1. Co-occurrence feature learning for skeleton based action recognition using regularised deep lstm networks;zhu;THIRTIETH AAAI Conference on Artificial Intelligence,2016

2. Two-stream convolutional networks for action recognition in videos;simonyan;Advances in neural information processing systems,2014

3. Towards good practices for very deep two-stream convnets;wang;arXiv preprintarXiv 1507 02159,2015

4. Contextual Action Recognition with R*CNN

5. Human Activity Recognition via Recognized Body Parts of Human Depth Silhouettes for Residents Monitoring Services at Smart Home

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2. Material handling machine activity recognition by context ensemble with gated recurrent units;Engineering Applications of Artificial Intelligence;2023-11

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