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 …
[HTML][HTML] Multi-modality approaches for medical support systems: A systematic review of the last decade
Healthcare traditionally relies on single-modality approaches, which limit the information
available for medical decisions. However, advancements in technology and the availability …
available for medical decisions. However, advancements in technology and the availability …
Human activity recognition based on multienvironment sensor data
With the development of artificial intelligence and the broad application of sensors, human
activity recognition (HAR) technologies based on noninvasive environmental sensors have …
activity recognition (HAR) technologies based on noninvasive environmental sensors have …
Multi-level feature fusion for multimodal human activity recognition in Internet of Healthcare Things
Abstract Human Activity Recognition (HAR) has become a crucial element for smart
healthcare applications due to the fast adoption of wearable sensors and mobile …
healthcare applications due to the fast adoption of wearable sensors and mobile …
[HTML][HTML] A systematic review of data fusion techniques for optimized structural health monitoring
Advancements in structural health monitoring (SHM) techniques have spiked in the past few
decades due to the rapid evolution of novel sensing and data transfer technologies. This …
decades due to the rapid evolution of novel sensing and data transfer technologies. This …
[HTML][HTML] Multi-source information fusion: Progress and future
Abstract Multi-Source Information Fusion (MSIF), as a comprehensive interdisciplinary field
based on modern information technology, has gained significant research value and …
based on modern information technology, has gained significant research value and …
Human activity recognition with smartphone and wearable sensors using deep learning techniques: A review
Human Activity Recognition (HAR) is a field that infers human activities from raw time-series
signals acquired through embedded sensors of smartphones and wearable devices. It has …
signals acquired through embedded sensors of smartphones and wearable devices. It has …
Deep-learning-enhanced multitarget detection for end–edge–cloud surveillance in smart IoT
Along with the rapid development of cloud computing, IoT, and AI technologies, cloud video
surveillance (CVS) has become a hotly discussed topic, especially when facing the …
surveillance (CVS) has become a hotly discussed topic, especially when facing the …
Vision-based human activity recognition: a survey
Human activity recognition (HAR) systems attempt to automatically identify and analyze
human activities using acquired information from various types of sensors. Although several …
human activities using acquired information from various types of sensors. Although several …
A practical tutorial on bagging and boosting based ensembles for machine learning: Algorithms, software tools, performance study, practical perspectives and …
Ensembles, especially ensembles of decision trees, are one of the most popular and
successful techniques in machine learning. Recently, the number of ensemble-based …
successful techniques in machine learning. Recently, the number of ensemble-based …