Human activity recognition using tools of convolutional neural networks: A state of the art review, data sets, challenges, and future prospects
Abstract Human Activity Recognition (HAR) plays a significant role in the everyday life of
people because of its ability to learn extensive high-level information about human activity …
people because of its ability to learn extensive high-level information about human activity …
[HTML][HTML] Trends in human activity recognition using smartphones
Recognizing human activities and monitoring population behavior are fundamental needs of
our society. Population security, crowd surveillance, healthcare support and living …
our society. Population security, crowd surveillance, healthcare support and living …
A multibranch CNN-BiLSTM model for human activity recognition using wearable sensor data
Human activity recognition (HAR) has become a significant area of research in human
behavior analysis, human–computer interaction, and pervasive computing. Recently, deep …
behavior analysis, human–computer interaction, and pervasive computing. Recently, deep …
[HTML][HTML] Unsupervised human detection with an embedded vision system on a fully autonomous UAV for search and rescue operations
Unmanned aerial vehicles (UAVs) play a primary role in a plethora of technical and scientific
fields owing to their wide range of applications. In particular, the provision of emergency …
fields owing to their wide range of applications. In particular, the provision of emergency …
[HTML][HTML] Ensem-HAR: An ensemble deep learning model for smartphone sensor-based human activity recognition for measurement of elderly health monitoring
Biomedical images contain a huge number of sensor measurements that can provide
disease characteristics. Computer-assisted analysis of such parameters aids in the early …
disease characteristics. Computer-assisted analysis of such parameters aids in the early …
[HTML][HTML] Human activity recognition from sensor data using spatial attention-aided CNN with genetic algorithm
A Sarkar, SKS Hossain, R Sarkar - Neural Computing and Applications, 2023 - Springer
Capturing time and frequency relationships of time series signals offers an inherent barrier
for automatic human activity recognition (HAR) from wearable sensor data. Extracting …
for automatic human activity recognition (HAR) from wearable sensor data. Extracting …
Dynamic hand gesture recognition based on signals from specialized data glove and deep learning algorithms
Y Dong, J Liu, W Yan - IEEE Transactions on Instrumentation …, 2021 - ieeexplore.ieee.org
Gesture recognition as a natural, convenient and recognizable way has been received more
and more attention on human-machine interaction (HMI) recently. However, visual-based …
and more attention on human-machine interaction (HMI) recently. However, visual-based …
Intelligent stress monitoring assistant for first responders
K Lai, SN Yanushkevich, VP Shmerko - IEEE Access, 2021 - ieeexplore.ieee.org
This paper describes a prototype of an intelligent Stress Monitoring Assistant (SMA),-the
next generation of stress detectors. The SMA is intended for the first responders and …
next generation of stress detectors. The SMA is intended for the first responders and …
Deep human activity recognition with localisation of wearable sensors
Automatic recognition of human activities using wearable sensors remains a challenging
problem due to high variability in inter-person gait and movements. Moreover, finding the …
problem due to high variability in inter-person gait and movements. Moreover, finding the …
Binarized neural network for edge intelligence of sensor-based human activity recognition
A wide diversity of sensors has been applied in human activity recognition. These sensors
generate enormous amounts of data during human activity monitoring. Server-based …
generate enormous amounts of data during human activity monitoring. Server-based …