A survey on unsupervised learning for wearable sensor-based activity recognition
Abstract Human Activity Recognition (HAR) is an essential task in various applications such
as pervasive healthcare, smart environment, and security and surveillance. The need to …
as pervasive healthcare, smart environment, and security and surveillance. The need to …
Robust human locomotion and localization activity recognition over multisensory
Human activity recognition (HAR) plays a pivotal role in various domains, including
healthcare, sports, robotics, and security. With the growing popularity of wearable devices …
healthcare, sports, robotics, and security. With the growing popularity of wearable devices …
Large scale foundation models for intelligent manufacturing applications: a survey
H Zhang, SD Semujju, Z Wang, X Lv, K Xu… - Journal of Intelligent …, 2025 - Springer
Although the applications of artificial intelligence especially deep learning have greatly
improved various aspects of intelligent manufacturing, they still face challenges for broader …
improved various aspects of intelligent manufacturing, they still face challenges for broader …
Human activity recognition from multiple sensors data using deep CNNs
Smart devices with sensors now enable continuous measurement of activities of daily living.
Accordingly, various human activity recognition (HAR) experiments have been carried out …
Accordingly, various human activity recognition (HAR) experiments have been carried out …
Human fall detection using 3D multi-stream convolutional neural networks with fusion
T Alanazi, G Muhammad - Diagnostics, 2022 - mdpi.com
Human falls, especially for elderly people, can cause serious injuries that might lead to
permanent disability. Approximately 20–30% of the aged people in the United States who …
permanent disability. Approximately 20–30% of the aged people in the United States who …
Human action recognition using an optical flow-gated recurrent neural network
D Giveki - International Journal of Multimedia Information …, 2024 - Springer
Recognizing various human actions in videos is considered a highly complicated problem,
which has many potential applications in solving real-world problems such as human …
which has many potential applications in solving real-world problems such as human …
Deep ontology-based human locomotor activity recognition system via multisensory devices
Recognition of human locomotor activities is crucial for monitoring the motion patterns.
Current studies for human locomotor activities recognition focused on detecting basic motion …
Current studies for human locomotor activities recognition focused on detecting basic motion …
A novel hybrid deep learning approach with GWO–WOA optimization technique for human activity recognition
Abstract The effectiveness of Human Activity Recognition (HAR) models can be largely
attributed to the components derived from domain expertise. The classification system swiftly …
attributed to the components derived from domain expertise. The classification system swiftly …
Deep SE-BiLSTM with IFPOA fine-tuning for human activity recognition using mobile and wearable sensors
Pervasive computing, human–computer interaction, human behavior analysis, and human
activity recognition (HAR) fields have grown significantly. Deep learning (DL)-based …
activity recognition (HAR) fields have grown significantly. Deep learning (DL)-based …
Attribute-wise reasoning reinforcement learning for pedestrian attribute retrieval
Y Wang, Z Hu, Z Ji - International Journal of Multimedia Information …, 2023 - Springer
Pedestrian attribute retrieval (PAR) aims at retrieving soft-biometric attributes of pedestrian
images from video surveillance. Despite advancements, PAR grapples with challenges …
images from video surveillance. Despite advancements, PAR grapples with challenges …