Transfer Learning and Hybrid Deep Convolutional Neural Networks Models for Autism Spectrum Disorder Classification From EEG Signals-Reference-Cited by-同舟云学术

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Transfer Learning and Hybrid Deep Convolutional Neural Networks Models for Autism Spectrum Disorder Classification From EEG Signals

Published:2024 Issue: Volume:12 Page:64510-64530
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Al-Qazzaz Noor Kamal¹^ORCID,Aldoori Alaa A.¹,Buniya Ali K.¹,Ali Sawal Hamid Bin Mohd²^ORCID,Ahmad Siti Anom³^ORCID

Affiliation:

1. Department of Biomedical Engineering, Al-Khwarizmi College of Engineering, University of Baghdad, Baghdad, Iraq

2. Department of Electrical Electronic and Systems Engineering, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia (UKM), Bangi, Selangor, Malaysia

3. Department of Electrical and Electronic Engineering, Faculty of Engineering, Universiti Putra Malaysia (UPM), Serdang, Selangor, Malaysia

Funder

Fundamental Research Grant Scheme (FRGS), Ministry of Higher Education, Malaysia

Universiti Kebangsaan Malaysia

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6287639/10380310/10520303.pdf?arnumber=10520303

Reference64 articles.

1. Machine learning (ML) for the diagnosis of autism spectrum disorder (ASD) using brain imaging

2. Deep Learning Algorithms to Identify Autism Spectrum Disorder in Children-Based Facial Landmarks

3. Peripheral Inflammatory Markers Contributing to Comorbidities in Autism

4. Global prevalence of autism: A systematic review update

5. EEG classification analysis for diagnosing autism spectrum disorder based on emotions;Harun;J. Telecommun., Electron. Comput. Eng.,2018

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