Lara: Creating a dataset for human activity recognition in logistics using semantic attributes
Optimizations in logistics require recognition and analysis of human activities. The potential
of sensor-based human activity recognition (HAR) in logistics is not yet well explored …
of sensor-based human activity recognition (HAR) in logistics is not yet well explored …
Improving deep learning for HAR with shallow LSTMs
Recent studies in Human Activity Recognition (HAR) have shown that Deep Learning
methods are able to outperform classical Machine Learning algorithms. One popular Deep …
methods are able to outperform classical Machine Learning algorithms. One popular Deep …
FOCAL: Contrastive learning for multimodal time-series sensing signals in factorized orthogonal latent space
This paper proposes a novel contrastive learning framework, called FOCAL, for extracting
comprehensive features from multimodal time-series sensing signals through self …
comprehensive features from multimodal time-series sensing signals through self …
Activity classification using accelerometers and machine learning for complex construction worker activities
Automated Construction worker activity classification has the potential to not only benefit the
worker performance in terms of productivity and safety, but also the overall project …
worker performance in terms of productivity and safety, but also the overall project …
SWL-Adapt: An unsupervised domain adaptation model with sample weight learning for cross-user wearable human activity recognition
Abstract In practice, Wearable Human Activity Recognition (WHAR) models usually face
performance degradation on the new user due to user variance. Unsupervised domain …
performance degradation on the new user due to user variance. Unsupervised domain …
Deep unsupervised domain adaptation with time series sensor data: A survey
Sensors are devices that output signals for sensing physical phenomena and are widely
used in all aspects of our social production activities. The continuous recording of physical …
used in all aspects of our social production activities. The continuous recording of physical …
A survey of deep learning based models for human activity recognition
NS Khan, MS Ghani - Wireless Personal Communications, 2021 - Springer
Abstract Human Activity Recognition (HAR) is a process of recognizing human activities
automatically based on streaming data obtained from various sensors, such as, inertial …
automatically based on streaming data obtained from various sensors, such as, inertial …
Giobalfusion: A global attentional deep learning framework for multisensor information fusion
The paper enhances deep-neural-network-based inference in sensing applications by
introducing a lightweight attention mechanism called the global attention module for multi …
introducing a lightweight attention mechanism called the global attention module for multi …
Federated learning on multimodal data: A comprehensive survey
With the growing awareness of data privacy, federated learning (FL) has gained increasing
attention in recent years as a major paradigm for training models with privacy protection in …
attention in recent years as a major paradigm for training models with privacy protection in …
Flame: Federated learning across multi-device environments
Federated Learning (FL) enables distributed training of machine learning models while
keeping personal data on user devices private. While we witness increasing applications of …
keeping personal data on user devices private. While we witness increasing applications of …