Automated FBSE-EWT based learning framework for detection of epileptic seizures using time-segmented EEG signals

A Anuragi, DS Sisodia, RB Pachori - Computers in Biology and Medicine, 2021 - Elsevier
Epilepsy is a neurological disorder that has severely affected many people's lives across the
world. Electroencephalogram (EEG) signals are used to characterize the brain's state and …

[HTML][HTML] Incorporating landslide spatial information and correlated features among conditioning factors for landslide susceptibility map**

X Yang, R Liu, M Yang, J Chen, T Liu, Y Yang… - Remote Sensing, 2021 - mdpi.com
This study proposed a new hybrid model based on the convolutional neural network (CNN)
for making effective use of historical datasets and producing a reliable landslide …

Feature Selection with Deep Belief Network for Epileptic Seizure Detection on EEG Signals.

S Cherukuvada, R Kayalvizhi - Computers, Materials & …, 2023 - search.ebscohost.com
The term Epilepsy refers to a most commonly occurring brain disorder after a migraine. Early
identification of incoming seizures significantly impacts the lives of people with Epilepsy …

EEG-based epileptic seizure detection using deep learning techniques: A survey

J Xu, K Yan, Z Deng, Y Yang, JX Liu, J Wang, S Yuan - Neurocomputing, 2024 - Elsevier
Epilepsy is a complex neurological disorder marked by recurrent seizures, often stemming
from abnormal discharge of the brain. Electroencephalogram (EEG) captures temporal and …

Identification and mitigation of phishing email attacks using deep learning

J Ramprasath, S Priyanka, R Manudev… - 2023 3rd International …, 2023 - ieeexplore.ieee.org
Internet security is seriously threatened by email-based internet phishing. The process of
completely hiding the sender information of a phishing mails is far less flexible than the …

Secured data transaction for agriculture harvesting using blockchain technology

J Ramprasath, MM Nishath… - … on Vision Towards …, 2023 - ieeexplore.ieee.org
One of the biggest sectors in the world is agriculture, and a lot of data is produced every day
in this industry. However, because there aren't adequate data management systems, this …

Towards fully automated detection of epileptic disorders: a novel CNSVM approach with Clough–Tocher interpolation

BM İpek, HO Altun, K Öztoprak - Biomedical Engineering …, 2022 - degruyter.com
Epilepsy is a neurological disorder requiring specialists to scrutinize medical data at
diagnosis. Diagnosis stage is both time consuming and challenging, requiring expertise in …

A New Classification Approach Based On Support Vector Regression For Epileptic Seizure Detection

E KINACI, H BAL, H KINACI - JOURNAL OF POLYTECHNIC …, 2024 - avesis.erciyes.edu.tr
Epileptik nöbet tespiti için destek vektör regresyon temelli yeni bir sınıflandırma yaklaşımı A new
classification appr Page 1 POLİTEKNİK DERGİSİ JOURNAL of POLYTECHNIC ISSN …

Epileptik Nöbet Tespiti İçin Destek Regresyon Temelli Yeni Bir Sınıflandırma Yaklaşımı

EB Kınacı, H Bal, H Kınacı - Politeknik Dergisi, 2024 - dergipark.org.tr
Sınıflandırma problemi araştırmacılar tarafından uzun zamandır incelenen bir konu olmasına
rağmen güncelliğini hala korumaktadır. Özellikle görüntü işleme ve hastalık tanısının …

Data mining with deep learning in biomedical data

K Singh, J Malhotra - Predictive Modeling in Biomedical Data Mining and …, 2022 - Elsevier
In the era of technological advances, the health-care sector is going through a ground-
breaking transition by shifting the traditional approach of physical examination of patients to …