Human fall is one of the very critical health issues, especially for elders and disabled people
living alone. The number of elder populations is increasing steadily worldwide. Therefore …

Vision-based fall detection systems have experienced fast development over the last years.
To determine the course of its evolution and help new researchers, the main audience of this …

Recurrent neural networks (RNNs) are widely utilized in time series forecasting tasks. In
practical applications, there are noises in real-life time series data. A model's generalization …

Video based fall detection accuracy has been largely improved due to the recent progress
on deep convolutional neural networks. However, there still exist some challenges, such as …

Falls are one of the most serious health risks faced by older adults worldwide, and they can
have a significant impact on their physical and mental well-being as well as their quality of …

Breast cancer is a heterogeneous disease, where molecular subtypes of breast cancer are
closely related to the treatment and prognosis. Therefore, the goal of this work is to …

Thermal imaging has recently come to light to measure high human body temperature
(fever) in responses to the global public health issues. This is normally achieved by very …

Fall detection is a vital task in health monitoring, as it allows the system to trigger an alert
and therefore enable faster interventions when a person experiences a fall. Although most …

Nowadays, smart environments (SEs) enable the monitoring of people with physical
disabilities by incorporating activity recognition. Thermal cameras are being incorporated as …

The field of human activity recognition has evolved significantly, driven largely by
advancements in Internet of Things (IoT) device technology, particularly in personal devices …