[HTML][HTML] An efficient and lightweight multiperson activity recognition framework for robot-assisted healthcare applications
Aging is inevitably associated with a decline in physical abilities and can pose challenges to
the social lives of elderly individuals. In long-term care facilities, group exercise is …
the social lives of elderly individuals. In long-term care facilities, group exercise is …
Towards Improving Breast Cancer Classification using an Adaptive Voting Ensemble Learning Algorithm
Over the past decade, breast cancer has been the most common type of cancer in women.
Different methods were proposed for breast cancer detection. These methods mainly classify …
Different methods were proposed for breast cancer detection. These methods mainly classify …
[PDF][PDF] Federated recognition mechanism based on enhanced temporal-spatial learning using mobile edge sensors for firefighters.
Abstract Background Interest in Human Action Recognition (HAR), which encompasses both
household and industrial settings, is growing. HAR describes a computer system's capacity …
household and industrial settings, is growing. HAR describes a computer system's capacity …
A novel hybrid strategy based on Swarm and Heterogeneous Federated Learning using model credibility awareness for activity recognition in cross-silo multistorey …
The novel HAR-SHFDL system leverages a Swarm Heterogeneous Federated Deep
Learning framework for smartphone-based Human Activity Recognition (HAR). Unlike …
Learning framework for smartphone-based Human Activity Recognition (HAR). Unlike …
Swarm Learning Empowered Federated Deep Learning for Seamless Smartphone-Based Activity Recognition
In the landscape of smartphone-based human activity recognition (S-HAR), adopting
Federated Deep Learning (FDL) introduces challenges, notably in communication …
Federated Deep Learning (FDL) introduces challenges, notably in communication …
Federated Active Learning with Transfer Learning: Empowering Edge Intelligence for Enhanced Lung Cancer Diagnosis
Federated Learning has emerged as a promising paradigm for collaborative model training
in healthcare. FL allows institutions to share knowledge without compromising patient …
in healthcare. FL allows institutions to share knowledge without compromising patient …
[HTML][HTML] Optimal smart contracts for controlling the environment in electric vehicles based on an Internet of Things network
The scientific community has recently focused on intelligent models for predicting and
optimizing EV energy management. Despite numerous studies in energy management …
optimizing EV energy management. Despite numerous studies in energy management …
Unraveling the Potential of Attentive Bi-LSTM for Accurate Obesity Prognosis: Advancing Public Health towards Sustainable Cities
H Ayub, MA Khan, S Shehryar Ali Naqvi, M Faseeh… - Bioengineering, 2024 - mdpi.com
The global prevalence of obesity presents a pressing challenge to public health and
healthcare systems, necessitating accurate prediction and understanding for effective …
healthcare systems, necessitating accurate prediction and understanding for effective …
Few-shot transfer learning for wearable IMU-based human activity recognition
Deep learning has proven to be highly effective for human activity recognition (HAR) when
large amount of labelled data is available for the target task. However, training a deep …
large amount of labelled data is available for the target task. However, training a deep …
[HTML][HTML] High-Performance Real-Time Human Activity Recognition Using Machine Learning
Human Activity Recognition (HAR) is a vital technology in domains such as healthcare,
fitness, and smart environments. This paper presents an innovative HAR system that …
fitness, and smart environments. This paper presents an innovative HAR system that …