Deep learning algorithms for human activity recognition using mobile and wearable sensor networks: State of the art and research challenges
Human activity recognition systems are developed as part of a framework to enable
continuous monitoring of human behaviours in the area of ambient assisted living, sports …
continuous monitoring of human behaviours in the area of ambient assisted living, sports …
[HTML][HTML] Transfer learning enhanced vision-based human activity recognition: a decade-long analysis
The discovery of several machine learning and deep learning techniques has paved the
way to extend the reach of humans in various real-world applications. Classical machine …
way to extend the reach of humans in various real-world applications. Classical machine …
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 …
Data fusion and multiple classifier systems for human activity detection and health monitoring: Review and open research directions
Activity detection and classification using different sensor modalities have emerged as
revolutionary technology for real-time and autonomous monitoring in behaviour analysis …
revolutionary technology for real-time and autonomous monitoring in behaviour analysis …
Multi-task self-supervised learning for human activity detection
Deep learning methods are successfully used in applications pertaining to ubiquitous
computing, pervasive intelligence, health, and well-being. Specifically, the area of human …
computing, pervasive intelligence, health, and well-being. Specifically, the area of human …
Smart devices are different: Assessing and mitigatingmobile sensing heterogeneities for activity recognition
A Stisen, H Blunck, S Bhattacharya… - Proceedings of the 13th …, 2015 - dl.acm.org
The widespread presence of motion sensors on users' personal mobile devices has
spawned a growing research interest in human activity recognition (HAR). However, when …
spawned a growing research interest in human activity recognition (HAR). However, when …
Convolutional neural networks for human activity recognition using mobile sensors
A variety of real-life mobile sensing applications are becoming available, especially in the
life-logging, fitness tracking and health monitoring domains. These applications use mobile …
life-logging, fitness tracking and health monitoring domains. These applications use mobile …
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 …
Selfhar: Improving human activity recognition through self-training with unlabeled data
Machine learning and deep learning have shown great promise in mobile sensing
applications, including Human Activity Recognition. However, the performance of such …
applications, including Human Activity Recognition. However, the performance of such …
Deep recurrent neural network for mobile human activity recognition with high throughput
In this paper, we propose a method of human activity recognition with high throughput from
raw accelerometer data applying a deep recurrent neural network (DRNN), and investigate …
raw accelerometer data applying a deep recurrent neural network (DRNN), and investigate …