[HTML][HTML] 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 review of multimodal human activity recognition with special emphasis on classification, applications, challenges and future directions
Human activity recognition (HAR) is one of the most important and challenging problems in
the computer vision. It has critical application in wide variety of tasks including gaming …
the computer vision. It has critical application in wide variety of tasks including gaming …
Deep learning for IoT big data and streaming analytics: A survey
In the era of the Internet of Things (IoT), an enormous amount of sensing devices collect
and/or generate various sensory data over time for a wide range of fields and applications …
and/or generate various sensory data over time for a wide range of fields and applications …
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 …
Human activity recognition using inertial, physiological and environmental sensors: A comprehensive survey
In the last decade, Human Activity Recognition (HAR) has become a vibrant research area,
especially due to the spread of electronic devices such as smartphones, smartwatches and …
especially due to the spread of electronic devices such as smartphones, smartwatches and …
Communication-efficient learning of deep networks from decentralized data
Modern mobile devices have access to a wealth of data suitable for learning models, which
in turn can greatly improve the user experience on the device. For example, language …
in turn can greatly improve the user experience on the device. For example, language …
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 …
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 …
Convolutional neural networks and long short-term memory for skeleton-based human activity and hand gesture recognition
In this work, we address human activity and hand gesture recognition problems using 3D
data sequences obtained from full-body and hand skeletons, respectively. To this aim, we …
data sequences obtained from full-body and hand skeletons, respectively. To this aim, we …
[HTML][HTML] Deep learning analysis of mobile physiological, environmental and location sensor data for emotion detection
The detection and monitoring of emotions are important in various applications, eg, to
enable naturalistic and personalised human-robot interaction. Emotion detection often …
enable naturalistic and personalised human-robot interaction. Emotion detection often …