Multi-sensor information fusion based on machine learning for real applications in human activity recognition: State-of-the-art and research challenges
This paper firstly introduces common wearable sensors, smart wearable devices and the key
application areas. Since multi-sensor is defined by the presence of more than one model or …
application areas. Since multi-sensor is defined by the presence of more than one model or …
A review on deep learning techniques for IoT data
Continuous growth in software, hardware and internet technology has enabled the growth of
internet-based sensor tools that provide physical world observations and data …
internet-based sensor tools that provide physical world observations and data …
A comprehensive review of computer vision in sports: Open issues, future trends and research directions
Recent developments in video analysis of sports and computer vision techniques have
achieved significant improvements to enable a variety of critical operations. To provide …
achieved significant improvements to enable a variety of critical operations. To provide …
A comprehensive survey on imputation of missing data in internet of things
The Internet of Things (IoT) is enabled by the latest developments in smart sensors,
communication technologies, and Internet protocols with broad applications. Collecting data …
communication technologies, and Internet protocols with broad applications. Collecting data …
A survey on video action recognition in sports: Datasets, methods and applications
To understand human behaviors, action recognition based on videos is a common
approach. Compared with image-based action recognition, videos provide much more …
approach. Compared with image-based action recognition, videos provide much more …
An end-to-end deep learning pipeline for football activity recognition based on wearable acceleration sensors
R Cuperman, KMB Jansen, MG Ciszewski - Sensors, 2022 - mdpi.com
Action statistics in sports, such as the number of sprints and jumps, along with the details of
the corresponding locomotor actions, are of high interest to coaches and players, as well as …
the corresponding locomotor actions, are of high interest to coaches and players, as well as …
Prototype machine learning algorithms from wearable technology to detect tennis stroke and movement actions
T Perri, M Reid, A Murphy, K Howle, R Duffield - Sensors, 2022 - mdpi.com
This study evaluated the accuracy of tennis-specific stroke and movement event detection
algorithms from a cervically mounted wearable sensor containing a triaxial accelerometer …
algorithms from a cervically mounted wearable sensor containing a triaxial accelerometer …
Hybrid lightweight Deep-learning model for Sensor-fusion basketball Shooting-posture recognition
J Fan, S Bi, R Xu, L Wang, L Zhang - Measurement, 2022 - Elsevier
Shooting-posture recognition is an important area in basketball technical movement
recognition domain. This paper proposes the squeeze convolutional gated attention (SCGA) …
recognition domain. This paper proposes the squeeze convolutional gated attention (SCGA) …
Sensor-based human activity recognition using graph LSTM and multi-task classification model
This paper explores human activities recognition from sensor-based multi-dimensional
streams. Recently, deep learning-based methods such as LSTM and CNN have achieved …
streams. Recently, deep learning-based methods such as LSTM and CNN have achieved …
Wearable sensors for activity recognition in ultimate frisbee using convolutional neural networks and transfer learning
In human activity recognition (HAR), activities are automatically recognized and classified
from a continuous stream of input sensor data. Although the scientific community has …
from a continuous stream of input sensor data. Although the scientific community has …