AIMC Topic: Human Activities
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Radar Signal Processing and Its Impact on Deep Learning-Driven Human Activity Recognition.
Sensors (Basel, Switzerland)
Jan 25, 2025
Human activity recognition (HAR) using radar technology is becoming increasingly valuable for applications in areas such as smart security systems, healthcare monitoring, and interactive computing. This study investigates the integration of convoluti...
Exploring the impact of natural and human activities on vegetation changes: An integrated analysis framework based on trend analysis and machine learning.
Journal of environmental management
Jan 17, 2025
Climate, human activities and terrain are crucial factors influencing vegetation changes. Despite their crucial role, there is a notable lack of research exploring the nonlinear relationships between them and vegetation changes, especially over exten...
In Shift and In Variance: Assessing the Robustness of HAR Deep Learning Models Against Variability.
Sensors (Basel, Switzerland)
Jan 13, 2025
Deep learning (DL)-based Human Activity Recognition (HAR) using wearable inertial measurement unit (IMU) sensors can revolutionize continuous health monitoring and early disease prediction. However, most DL HAR models are untested in their robustness...
Human-Centric Transformer for Domain Adaptive Action Recognition.
IEEE transactions on pattern analysis and machine intelligence
Jan 9, 2025
We study the domain adaptation task for action recognition, namely domain adaptive action recognition, which aims to effectively transfer action recognition power from a label-sufficient source domain to a label-free target domain. Since actions are ...
Applying MLP-Mixer and gMLP to Human Activity Recognition.
Sensors (Basel, Switzerland)
Jan 7, 2025
The development of deep learning has led to the proposal of various models for human activity recognition (HAR). Convolutional neural networks (CNNs), initially proposed for computer vision tasks, are examples of models applied to sensor data. Recent...
SemiHAR: Improving Semisupervised Human Activity Recognition via Multitask Learning.
IEEE transactions on neural networks and learning systems
Jan 7, 2025
Semisupervised human activity recognition (SemiHAR) has attracted attention in recent years from various domains, such as digital health and ambient intelligence. Currently, it still faces two challenges. For one thing, discriminative features may ex...
SVM directed machine learning classifier for human action recognition network.
Scientific reports
Jan 3, 2025
Understanding human behavior and human action recognition are both essential components of effective surveillance video analysis for the purpose of guaranteeing public safety. However, existing approaches such as three-dimensional convolutional neura...
Logical reasoning for human activity recognition based on multisource data from wearable device.
Scientific reports
Jan 2, 2025
Smart wearable devices detection and recording of people's everyday activities is critical for health monitoring, helping persons with disabilities, and providing care for the elderly. Most of the research that is being conducted uses a machine learn...
Vision Sensor for Automatic Recognition of Human Activities via Hybrid Features and Multi-Class Support Vector Machine.
Sensors (Basel, Switzerland)
Jan 1, 2025
Over recent years, automated Human Activity Recognition (HAR) has been an area of concern for many researchers due to its widespread application in surveillance systems, healthcare environments, and many more. This has led researchers to develop cohe...
Identifying human activities causing water pollution based on microbial community sequencing and source classifier machine learning.
Environment international
Dec 24, 2024
Identifying and differentiating human activities is crucial for effectively preventing the threats posed by environmental pollution to aquatic ecosystems and human health. Machine learning (ML) is a powerful analytical tool for tracking human impacts...
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