A Survey on State-of-the-art Deep Learning Applications and Challenges
MHM Noor, AO Ige - arXiv preprint arXiv:2403.17561, 2024 - arxiv.org
Deep learning, a branch of artificial intelligence, is a data-driven method that uses multiple
layers of interconnected units (neurons) to learn intricate patterns and representations …
layers of interconnected units (neurons) to learn intricate patterns and representations …
Intelligent Adaptive Real-Time Monitoring and Recognition System for Human Activities
Numerous sensors on smart devices have made it possible to automatically recognize
human movement, which might be helpful for intelligent applications like elder care, smart …
human movement, which might be helpful for intelligent applications like elder care, smart …
[PDF][PDF] AI-Enabled Scalable Smartphone Photonic Sensing System for Remote Healthcare Monitoring
Remote healthcare monitoring is a crucial component in the field of medical Internet of
Things (IoT), which effectively achieves remote monitoring, collection, and transmission of …
Things (IoT), which effectively achieves remote monitoring, collection, and transmission of …
Deep Transfer Learning for Detection of Upper and Lower Body Movements: Transformer with Convolutional Neural Network
K Lacroix, D Gholamiangonabadi… - IEEE Sensors …, 2024 - ieeexplore.ieee.org
When humans repeat the same motion, the tendons, muscles, and nerves can be damaged,
causing repetitive stress injuries (RSIs). If the repetitive motions that lead to RSI are …
causing repetitive stress injuries (RSIs). If the repetitive motions that lead to RSI are …
[HTML][HTML] Generisch-Net: A Generic Deep Model for Analyzing Human Motion with Wearable Sensors in the Internet of Health Things
The Internet of Health Things (IoHT) is a broader version of the Internet of Things. The main
goal is to intervene autonomously from geographically diverse regions and provide low-cost …
goal is to intervene autonomously from geographically diverse regions and provide low-cost …
Enhancing Human Activity Recognition in Wrist-Worn Sensor Data Through Compensation Strategies for Sensor Displacement
Human man Activity Recognition (HAR) using wearable sensors, particularly wrist-worn
devices, has garnered significant research interest. However, challenges such as sensor …
devices, has garnered significant research interest. However, challenges such as sensor …
Sensor-Based Gymnastics Action Recognition Using Time-Series Images and a Lightweight Feature Fusion Network
With the development of microelectromechanical systems (MEMS) and artificial intelligence
technology, the application of wearable devices in human motion capture and recognition …
technology, the application of wearable devices in human motion capture and recognition …
Dynamic Inclination Identification Methods for Mine-Use Monorail Crane Transport Robots Under Dual Operating Conditions
Z Liu, W Wu, J Li, C Zheng, G Wang - IEEE Sensors Journal, 2024 - ieeexplore.ieee.org
Monorail cranes are essential in auxiliary transportation within deep mines. In order to
ensure the stability and safety of the monorail cranes under different traveling conditions of …
ensure the stability and safety of the monorail cranes under different traveling conditions of …
Mukhtasir-Khail-Net: An Ultra-Efficient Convolutional Neural Network for Sports Activity Recognition with Wearable Inertial Sensors
The current prevalent approach of the Internet of Health and Medical Things entails
proactively preventing disease onset through routine monitoring of individuals' physical …
proactively preventing disease onset through routine monitoring of individuals' physical …
A Novel Human Activity Recognition Model
With the continuous improvement of the living standard, people have changed their concept
of disease treatment to health management. However, most of the current health …
of disease treatment to health management. However, most of the current health …