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 …
Sensor-based human activity recognition with spatio-temporal deep learning
Human activity recognition (HAR) remains a challenging yet crucial problem to address in
computer vision. HAR is primarily intended to be used with other technologies, such as the …
computer vision. HAR is primarily intended to be used with other technologies, such as the …
Human activity recognition with smartphone sensors using deep learning neural networks
CA Ronao, SB Cho - Expert systems with applications, 2016 - Elsevier
Human activities are inherently translation invariant and hierarchical. Human activity
recognition (HAR), a field that has garnered a lot of attention in recent years due to its high …
recognition (HAR), a field that has garnered a lot of attention in recent years due to its high …
Temporal-channel convolution with self-attention network for human activity recognition using wearable sensors
E Essa, IR Abdelmaksoud - Knowledge-Based Systems, 2023 - Elsevier
Human activity recognition (HAR) is an essential task in many applications such as health
monitoring, rehabilitation, and sports training. Sensor-based HAR has received increasing …
monitoring, rehabilitation, and sports training. Sensor-based HAR has received increasing …
Human activity recognition based on multienvironment sensor data
With the development of artificial intelligence and the broad application of sensors, human
activity recognition (HAR) technologies based on noninvasive environmental sensors have …
activity recognition (HAR) technologies based on noninvasive environmental sensors have …
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 …
The layer-wise training convolutional neural networks using local loss for sensor-based human activity recognition
Recently, deep learning, which are able to extract automatically features from data, has
achieved state-of-the-art performance across a variety of sensor based human activity …
achieved state-of-the-art performance across a variety of sensor based human activity …
Human activity recognition based on smartphone and wearable sensors using multiscale DCNN ensemble
Abstract Sensor-based Human Activity Recognition (sensor-based HAR) has been used in
many real-world applications providing valuable knowledge to many areas, such as human …
many real-world applications providing valuable knowledge to many areas, such as human …
Two-stream transformer network for sensor-based human activity recognition
S Xiao, S Wang, Z Huang, Y Wang, H Jiang - Neurocomputing, 2022 - Elsevier
Abstract Human Activity Recognition (HAR) based on wearable devices has always been a
hot topic in health applications, human-object interaction, and smart homes. Despite …
hot topic in health applications, human-object interaction, and smart homes. Despite …
Human activity recognition using wearable sensors by heterogeneous convolutional neural networks
Recent researches on sensor based human activity recognition (HAR) are mostly devoted to
designing various network architectures to enhance their feature representation capacity for …
designing various network architectures to enhance their feature representation capacity for …