Deep learning-based human activity recognition using CNN, ConvLSTM, and LRCN-Reference-Cited by-同舟云学术

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Deep learning-based human activity recognition using CNN, ConvLSTM, and LRCN

Published:2024 Issue: Volume:5 Page:259-268
ISSN:2666-3074
Container-title:International Journal of Cognitive Computing in Engineering
language:en
Short-container-title:International Journal of Cognitive Computing in Engineering

Author:

Uddin Md. Ashraf^ORCID,Talukder Md. Alamin^ORCID,Uzzaman Muhammad Sajib,Debnath Chandan,Chanda Moumita,Paul Souvik,Islam Md. Manowarul,Khraisat Ansam,Alazab Ammar,Aryal Sunil

Publisher

Elsevier BV

Reference32 articles.

1. Prevalence and characteristics of dementia in Parkinson disease: An 8-year prospective study;Aarsland;Archives of Neurology,2003

2. IoT wearable sensor and deep learning: An integrated approach for personalized human activity recognition in a smart home environment;Bianchi;IEEE Internet of Things Journal,2019

3. An improved approach for prediction of Parkinson’s disease using machine learning techniques;Challa,2016

4. Channel attention-based approach with autoencoder network for human action recognition in low-resolution frames;Dastbaravardeh;International Journal of Intelligent Systems,2024

5. Brainnet: precision brain tumor classification with optimized efficientnet architecture;Islam;International Journal of Intelligent Systems,2024

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