Due to the rapid development of artificial intelligence, seizure detection has achieved great
success in terms of accuracy and speed. However, low-power seizure detection algorithms …

The field of signal processing using machine and deep learning algorithms has undergone
significant growth in the last few years, with a wide scope of practical applications for …

Epilepsy is a neurological disease with one of the highest rates of incidence worldwide.
Although EEG is a crucial tool for its diagnosis, the manual detection of epileptic seizures is …

Objective To develop deep learning methods with high accuracy for segmenting irregular
corneas and detecting the tear fluid reservoir (TFR) boundary under the scleral lens …

Wearable devices with continuous monitoring capabilities are critical for the daily detection
of epileptic seizures, as they provide users with accurate and comprehensible analytical …

Automatic seizure detection technology has important implications for reducing the workload
of neurologists for epilepsy diagnosis and treatment. Due to the unpredictable nature of …

In this article, a kind of second-order neural networks with variable coefficients and
distributed delays are discussed. At first, new lemmas about fixed/preassigned-time …

The electrical activity of the brain can be monitored using the electroencephalogram (EEG),
which can be used in the detection of seizures. This paper proposes an epileptic seizure …

Deep learning models have recently shown great success in classifying epileptic patients
using EEG recordings. Unfortunately, classification-based methods lack a sound mechanism …

There are a number of technologies that might help farmers increase yields and decrease
losses, but two of the most important are precision farming and accurate weather forecasts …