– Researchers have developed a convolutional neural network (CNN) model, a type of deep learning model, for classifying epileptic seizures that is designed to provide maximum accuracy and minor computational complexity, according to a study published in Soft Computing.
The researchers developed their algorithm by integrating CNN architecture with a hierarchical attention mechanism, which was expected to enhance the model’s performance. The model comprises three parts: a feature extraction layer, a hierarchical attention layer, and a classification layer.
The model, which also uses a support vector machine (SVM) algorithm, analyzes a feature map obtained from the raw EEG signal and determines whether the EEGs it was taken from are “healthy” or “seizure.”
Sécurité des mots de passe : bonnes pratiques pour éviter les failles La sécurité des…
Ransomware : comment prévenir et réagir face à une attaque Le ransomware est l’une des…
Cybersécurité et e-commerce : protéger vos clients et vos ventes En 2025, les sites e-commerce…
Les ransomwares : comprendre et se défendre contre cette menace En 2025, les ransomwares représentent…
RGPD et cybersécurité : comment rester conforme en 2025 Depuis sa mise en application en…
VPN : un outil indispensable pour protéger vos données Le VPN, ou « Virtual Private…
This website uses cookies.