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Human Activities

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Employment of Ensemble Machine Learning Methods for Human Activity Recognition.

Journal of healthcare engineering
The endeavor to detect human activities and behaviors is targeted as a real-time detection mechanism that tends to predict the form of human motions and actions. Though sensors like accelerometer and gyroscopes are noticeable in human motion detectio...

A Multimodal Data Processing System for LiDAR-Based Human Activity Recognition.

IEEE transactions on cybernetics
Increasingly, the task of detecting and recognizing the actions of a human has been delegated to some form of neural network processing camera or wearable sensor data. Due to the degree to which the camera can be affected by lighting and wearable sen...

Detecting Human Actions in Drone Images Using YoloV5 and Stochastic Gradient Boosting.

Sensors (Basel, Switzerland)
Human action recognition and detection from unmanned aerial vehicles (UAVs), or drones, has emerged as a popular technical challenge in recent years, since it is related to many use case scenarios from environmental monitoring to search and rescue. I...

Lifelong Adaptive Machine Learning for Sensor-Based Human Activity Recognition Using Prototypical Networks.

Sensors (Basel, Switzerland)
Continual learning (CL), also known as lifelong learning, is an emerging research topic that has been attracting increasing interest in the field of machine learning. With human activity recognition (HAR) playing a key role in enabling numerous real-...

A Deep Sequence Learning Framework for Action Recognition in Small-Scale Depth Video Dataset.

Sensors (Basel, Switzerland)
Depth video sequence-based deep models for recognizing human actions are scarce compared to RGB and skeleton video sequences-based models. This scarcity limits the research advancements based on depth data, as training deep models with small-scale da...

Human activity recognition using tools of convolutional neural networks: A state of the art review, data sets, challenges, and future prospects.

Computers in biology and medicine
Human Activity Recognition (HAR) plays a significant role in the everyday life of people because of its ability to learn extensive high-level information about human activity from wearable or stationary devices. A substantial amount of research has b...

Rich learning representations for human activity recognition: How to empower deep feature learning for biological time series.

Journal of biomedical informatics
Deep learning versus feature engineering has drawn significant attention specifically for applications where expertly crafted features have been used for decades. Human activity recognition is no exception where statistical and motion specific featur...

Human Activity Recognition: Review, Taxonomy and Open Challenges.

Sensors (Basel, Switzerland)
Nowadays, Human Activity Recognition (HAR) is being widely used in a variety of domains, and vision and sensor-based data enable cutting-edge technologies to detect, recognize, and monitor human activities. Several reviews and surveys on HAR have alr...

Device-Free Multi-Location Human Activity Recognition Using Deep Complex Network.

Sensors (Basel, Switzerland)
Wi-Fi-based human activity recognition has attracted broad attention for its advantages, which include being device-free, privacy-protected, unaffected by light, etc. Owing to the development of artificial intelligence techniques, existing methods ha...

HHI-AttentionNet: An Enhanced Human-Human Interaction Recognition Method Based on a Lightweight Deep Learning Model with Attention Network from CSI.

Sensors (Basel, Switzerland)
Nowadays WiFi based human activity recognition (WiFi-HAR) has gained much attraction in an indoor environment due to its various benefits, including privacy and security, device free sensing, and cost-effectiveness. Recognition of human-human interac...