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[HTML][HTML] Human activity recognition: Review, taxonomy and open challenges
Nowadays, Human Activity Recognition (HAR) is being widely used in a variety of domains,
and vision and sensor-based data enable cutting-edge technologies to detect, recognize …
and vision and sensor-based data enable cutting-edge technologies to detect, recognize …
[HTML][HTML] Human activity recognition with smartphone-integrated sensors: A survey
Abstract Human Activity Recognition (HAR) is an essential area of research related to the
ability of smartphones to retrieve information through embedded sensors and recognize the …
ability of smartphones to retrieve information through embedded sensors and recognize the …
GRU-INC: An inception-attention based approach using GRU for human activity recognition
Abstract Human Activity Recognition (HAR) is very useful for the clinical applications, and
many machine learning algorithms have been successfully implemented to achieve high …
many machine learning algorithms have been successfully implemented to achieve high …
[HTML][HTML] Human activity recognition based on residual network and BiLSTM
Y Li, L Wang - Sensors, 2022 - mdpi.com
Due to the wide application of human activity recognition (HAR) in sports and health, a large
number of HAR models based on deep learning have been proposed. However, many …
number of HAR models based on deep learning have been proposed. However, many …
Recognizing sports activities from video frames using deformable convolution and adaptive multiscale features
Automated techniques for evaluating sports activities inside dynamic frames are highly
dependent on advanced sports analysis by smart machines. The monitoring of individuals …
dependent on advanced sports analysis by smart machines. The monitoring of individuals …
A cybertwin based multimodal network for ecg patterns monitoring using deep learning
In next-generation network architecture, the Cybertwin drove the sixth generation of cellular
networks sixth-generation (6G) to play an active role in many applications, such as …
networks sixth-generation (6G) to play an active role in many applications, such as …
A smartphone-based adaptive recognition and real-time monitoring system for human activities
Human activity recognition (HAR) using smartphones provides significant healthcare
guidance for telemedicine and long-term treatment. Machine learning and deep learning …
guidance for telemedicine and long-term treatment. Machine learning and deep learning …
[HTML][HTML] Wearable sensor-based human activity recognition with hybrid deep learning model
It is undeniable that mobile devices have become an inseparable part of human's daily
routines due to the persistent growth of high-quality sensor devices, powerful computational …
routines due to the persistent growth of high-quality sensor devices, powerful computational …
Neural fuzzy approximation enhanced autonomous tracking control of the wheel-legged robot under uncertain physical interaction
The accuracy of trajectory tracking and stable operation with heavy load are the main
challenges of parallel mechanism for wheel-legged robots, especially in complex road …
challenges of parallel mechanism for wheel-legged robots, especially in complex road …
Convae-lstm: Convolutional autoencoder long short-term memory network for smartphone-based human activity recognition
The self-regulated recognition of human activities from time-series smartphone sensor data
is a growing research area in smart and intelligent health care. Deep learning (DL) …
is a growing research area in smart and intelligent health care. Deep learning (DL) …