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Effect of different modalities of facial images on ASD diagnosis using deep learning-based neural network

This paper aims to investigate the effectiveness of different modalities of facial images for diagnosing Autism Spectrum Disorder (ASD) using deep learning-based neural networks. The motivation behind this study is the potential of advanced technologies to aid in accurately diagnosing ASD. The resea...

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Main Authors: Alam, Mohammad Shafiul, Tasneem, Zabina, Khan, Sher Afghan, Rashid, Muhammad Mahbubur
Format: Article
Language:English
English
Published: SEMARAK ILMU PUBLISHING 2023
Subjects:
TK4001 Applications of electric power
Online Access:http://irep.iium.edu.my/107341/7/107341_Effect%20of%20different%20modalities%20of%20facial%20images%20on%20ASD.pdf
http://irep.iium.edu.my/107341/13/107341_Effect%20of%20Different%20Modalities%20of%20Facial%20Images%20on%20ASD_Scopus.pdf
http://irep.iium.edu.my/107341/
https://semarakilmu.com.my/journals/index.php/applied_sciences_eng_tech/article/view/3854
https://doi.org/10.37934/araset.32.3.5974
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spelling my.iium.irep.1073412023-12-29T01:20:23Z http://irep.iium.edu.my/107341/ Effect of different modalities of facial images on ASD diagnosis using deep learning-based neural network Alam, Mohammad Shafiul Tasneem, Zabina Khan, Sher Afghan Rashid, Muhammad Mahbubur TK4001 Applications of electric power This paper aims to investigate the effectiveness of different modalities of facial images for diagnosing Autism Spectrum Disorder (ASD) using deep learning-based neural networks. The motivation behind this study is the potential of advanced technologies to aid in accurately diagnosing ASD. The research revolves around the need to explore the performance of deep learning models on different modalities of facial images and to identify the challenges and potential solutions associated with each modality. The methodology involves training and testing the models on the respective datasets and analyzing their accuracy and performance. ResNet50V2 achieved a 100% accuracy on the 2D test dataset, while Exception achieved an accuracy of 93.75% on the 3D test set. The detection accuracy suggests that neural networks-based deep learning methods have the potential to diagnose ASD using facial images accurately. However, the models perform better on 2D data, highlighting the need for additional training on larger 3D datasets to improve accuracy on 3D images. The study contributes to the field by providing insights into the performance of different modalities of facial images, emphasizing the need for robust datasets, and suggesting future research directions to enhance the accuracy and efficiency of ASD diagnosis using deep learning techniques. SEMARAK ILMU PUBLISHING 2023-10-03 Article PeerReviewed application/pdf en http://irep.iium.edu.my/107341/7/107341_Effect%20of%20different%20modalities%20of%20facial%20images%20on%20ASD.pdf application/pdf en http://irep.iium.edu.my/107341/13/107341_Effect%20of%20Different%20Modalities%20of%20Facial%20Images%20on%20ASD_Scopus.pdf Alam, Mohammad Shafiul and Tasneem, Zabina and Khan, Sher Afghan and Rashid, Muhammad Mahbubur (2023) Effect of different modalities of facial images on ASD diagnosis using deep learning-based neural network. Journal of Advanced Research in Applied Sciences and Engineering Technology, 32 (3). pp. 59-74. ISSN 2462-1943 https://semarakilmu.com.my/journals/index.php/applied_sciences_eng_tech/article/view/3854 https://doi.org/10.37934/araset.32.3.5974
institution Universiti Islam Antarabangsa Malaysia
building IIUM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider International Islamic University Malaysia
content_source IIUM Repository (IREP)
url_provider http://irep.iium.edu.my/
language English
English
topic TK4001 Applications of electric power
spellingShingle TK4001 Applications of electric power
Alam, Mohammad Shafiul
Tasneem, Zabina
Khan, Sher Afghan
Rashid, Muhammad Mahbubur
Effect of different modalities of facial images on ASD diagnosis using deep learning-based neural network
description This paper aims to investigate the effectiveness of different modalities of facial images for diagnosing Autism Spectrum Disorder (ASD) using deep learning-based neural networks. The motivation behind this study is the potential of advanced technologies to aid in accurately diagnosing ASD. The research revolves around the need to explore the performance of deep learning models on different modalities of facial images and to identify the challenges and potential solutions associated with each modality. The methodology involves training and testing the models on the respective datasets and analyzing their accuracy and performance. ResNet50V2 achieved a 100% accuracy on the 2D test dataset, while Exception achieved an accuracy of 93.75% on the 3D test set. The detection accuracy suggests that neural networks-based deep learning methods have the potential to diagnose ASD using facial images accurately. However, the models perform better on 2D data, highlighting the need for additional training on larger 3D datasets to improve accuracy on 3D images. The study contributes to the field by providing insights into the performance of different modalities of facial images, emphasizing the need for robust datasets, and suggesting future research directions to enhance the accuracy and efficiency of ASD diagnosis using deep learning techniques.
format Article
author Alam, Mohammad Shafiul
Tasneem, Zabina
Khan, Sher Afghan
Rashid, Muhammad Mahbubur
author_facet Alam, Mohammad Shafiul
Tasneem, Zabina
Khan, Sher Afghan
Rashid, Muhammad Mahbubur
author_sort Alam, Mohammad Shafiul
title Effect of different modalities of facial images on ASD diagnosis using deep learning-based neural network
title_short Effect of different modalities of facial images on ASD diagnosis using deep learning-based neural network
title_full Effect of different modalities of facial images on ASD diagnosis using deep learning-based neural network
title_fullStr Effect of different modalities of facial images on ASD diagnosis using deep learning-based neural network
title_full_unstemmed Effect of different modalities of facial images on ASD diagnosis using deep learning-based neural network
title_sort effect of different modalities of facial images on asd diagnosis using deep learning-based neural network
publisher SEMARAK ILMU PUBLISHING
publishDate 2023
url http://irep.iium.edu.my/107341/7/107341_Effect%20of%20different%20modalities%20of%20facial%20images%20on%20ASD.pdf
http://irep.iium.edu.my/107341/13/107341_Effect%20of%20Different%20Modalities%20of%20Facial%20Images%20on%20ASD_Scopus.pdf
http://irep.iium.edu.my/107341/
https://semarakilmu.com.my/journals/index.php/applied_sciences_eng_tech/article/view/3854
https://doi.org/10.37934/araset.32.3.5974
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score 13.211869

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