With the acceleration of the pace of work and life, people are facing more and more
pressure, which increases the probability of suffering from depression. However, many …

Depression has become one of the most common mental illnesses in the world. For better
prediction and diagnosis, methods of automatic depression recognition based on speech …

To overcome the shortcomings in current study of oil well production prediction, we propose
a combined model (CNN-LSTM-SA) with the convolutional neural network (CNN), the long …

Designing an electricity theft cyberattack detector for the advanced metering infrastructures
(AMIs) is challenging due to the limited availability of electricity theft datasets (ie, malicious …

At present, there have been many studies on the methods of using the deep learning
regression model to assess depression level based on behavioral signals (facial …

Depression is a common mental illness that affects the physical and mental health of
hundreds of millions of people around the world. Therefore, designing an efficient and …

Data-driven electricity theft detectors rely on customers' reported energy consumption
readings to detect malicious behavior. One common implicit assumption in such detectors is …

Millions of people are suffering from mental illness due to unavailability of early treatment
and services for depression detection. It is the major reason for anxiety disorder, bipolar …

Paralinguistic speech processing is important in addressing many issues, such as sentiment
and neurocognitive disorder analyses. Recently, Transformer has achieved remarkable …

Background In this modern era, depression is one of the most prevalent mental disorders
from which millions of individuals are affected today. The symptoms of depression are …