A review of state-of-the-art techniques for abnormal human activity recognition
C Dhiman, DK Vishwakarma - Engineering Applications of Artificial …, 2019 - Elsevier
The concept of intelligent visual identification of abnormal human activity has raised the
standards of surveillance systems, situation cognizance, homeland safety and smart …
standards of surveillance systems, situation cognizance, homeland safety and smart …
Applying machine learning for sensor data analysis in interactive systems: Common pitfalls of pragmatic use and ways to avoid them
T PlÖtz - ACM Computing Surveys (CSUR), 2021 - dl.acm.org
With the widespread proliferation of (miniaturized) sensing facilities and the massive growth
and popularity of the field of machine learning (ML) research, new frontiers in automated …
and popularity of the field of machine learning (ML) research, new frontiers in automated …
Deep, convolutional, and recurrent models for human activity recognition using wearables
Human activity recognition (HAR) in ubiquitous computing is beginning to adopt deep
learning to substitute for well-established analysis techniques that rely on hand-crafted …
learning to substitute for well-established analysis techniques that rely on hand-crafted …
Ensembles of deep lstm learners for activity recognition using wearables
Recently, deep learning (DL) methods have been introduced very successfully into human
activity recognition (HAR) scenarios in ubiquitous and wearable computing. Especially the …
activity recognition (HAR) scenarios in ubiquitous and wearable computing. Especially the …
Pantomime: Mid-air gesture recognition with sparse millimeter-wave radar point clouds
We introduce Pantomime, a novel mid-air gesture recognition system exploiting spatio-
temporal properties of millimeter-wave radio frequency (RF) signals. Pantomime is …
temporal properties of millimeter-wave radio frequency (RF) signals. Pantomime is …
Assessing the state of self-supervised human activity recognition using wearables
The emergence of self-supervised learning in the field of wearables-based human activity
recognition (HAR) has opened up opportunities to tackle the most pressing challenges in the …
recognition (HAR) has opened up opportunities to tackle the most pressing challenges in the …
CrossCheck: toward passive sensing and detection of mental health changes in people with schizophrenia
Early detection of mental health changes in individuals with serious mental illness is critical
for effective intervention. CrossCheck is the first step towards the passive monitoring of …
for effective intervention. CrossCheck is the first step towards the passive monitoring of …
Bridge infrastructure asset management system: Comparative computational machine learning approach for evaluating and predicting deck deterioration conditions
R Assaad, IH El-Adaway - Journal of Infrastructure Systems, 2020 - ascelibrary.org
Bridge infrastructure asset management system is a prevailing approach toward having an
effective and efficient procedure for monitoring bridges through their different development …
effective and efficient procedure for monitoring bridges through their different development …
Optimising sampling rates for accelerometer-based human activity recognition
Real-world deployments of accelerometer-based human activity recognition systems need
to be carefully configured regarding the sampling rate used for measuring acceleration …
to be carefully configured regarding the sampling rate used for measuring acceleration …
Deep learning based multimodal complex human activity recognition using wearable devices
L Chen, X Liu, L Peng, M Wu - Applied Intelligence, 2021 - Springer
Wearable device based human activity recognition, as an important field of ubiquitous and
mobile computing, is drawing more and more attention. Compared with simple human …
mobile computing, is drawing more and more attention. Compared with simple human …