Neonatal seizure detection from minimized EEG channels using polynomial compact support distribution and VGG19-BiLSTM hybrid model-Reference-Cited by-同舟云学术

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Neonatal seizure detection from minimized EEG channels using polynomial compact support distribution and VGG19-BiLSTM hybrid model

Published:2024-04-21 Issue: Volume: Page:1-6
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Container-title:2024 8th International Conference on Image and Signal Processing and their Applications (ISPA)
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Author:

Larbi Arezki¹,Abed Mansour¹,Nahi Ahmed¹,Ouahabi Abdeldjalil²

Affiliation:

1. University of Mostaganem Abdelhamid Ibn Badis (UMAB),Faculty of Science and Technology,Electrical Engineering Department and Laboratory of Signals and Systems (LSS),Mostaganem,Algeria

2. Université de Tours,UMR 1253, iBrain, INSERM,Tours,France,37000

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10536721/10536698/10536771.pdf?arnumber=10536771

Reference20 articles.

1. Neonatal seizure;Krawiec,2022

2. Why monitor the neonatal brain—that is the important question

3. Deep Convolutional Gated Recurrent Unit Combined with Attention Mechanism to Classify Pre-Ictal from Interictal EEG with Minimized Number of Channels

4. An overview of deep learning techniques for epileptic seizures detection and prediction based on neuroimaging modalities: Methods, challenges, and future works

5. Cross-Subject Seizure Detection in EEGs Using Deep Transfer Learning

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