Please use this identifier to cite or link to this item:
https://hdl.handle.net/1959.11/59731
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DC Field | Value | Language |
---|---|---|
dc.contributor.author | Nawer, Nafisa | en |
dc.contributor.author | Parvez, Mohammad Zavid | en |
dc.contributor.author | Iqbal Hossain, Muhammad | en |
dc.contributor.author | Barua, Prabal Datta | en |
dc.contributor.author | Rahim, Mia | en |
dc.contributor.author | Chakraborty, Subrata | en |
local.source.editor | Editor(s): Kevin Daimi, Abeer Al Sadoon | en |
dc.date.accessioned | 2024-05-23T01:06:25Z | - |
dc.date.available | 2024-05-23T01:06:25Z | - |
dc.date.issued | 2023-06-17 | - |
dc.identifier.citation | Proceedings of the Second International Conference on Innovations in Computing Research (ICR’23), v.721, p. 165-174 | en |
dc.identifier.isbn | 978-3-031-35307-9 | en |
dc.identifier.isbn | 978-3-031-35308-6 | en |
dc.identifier.uri | https://hdl.handle.net/1959.11/59731 | - |
dc.description.abstract | <p>Approximately 1 in 44 children worldwide has been identified as having Autism Spectrum Disorder (ASD), according to the Centers for Disease Control and Prevention (CDC). The term ‘ASD’ is used to characterize a collection of repetitive sensory-motor activities with strong hereditary foundations. Children with autism have a higher-than-average rate of motor impairments, which causes them to struggle with handwriting. Therefore, they generally perform worse on handwriting tasks compared to typically developing children of the same age. As a result, the purpose of this research is to identify autistic children by a comparison of their handwriting to that of typically developing children. Consequently, we investigated state-of-the-art methods for identifying ASD and evaluated whether or not handwriting might serve as bio-markers for ASD modeling. In this context, we presented a novel dataset comprised of the handwritten texts of children aged 7 to 10. Additionally, three pre-trained Transfer Learning frameworks: InceptionV3, VGG19, Xception were applied to achieve the best level of accuracy possible. We have evaluated the models on a number of quantitative performance evaluation metrics and demonstrated that Xception shows the best outcome with an accuracy of 98%.</p> | en |
dc.language | en | en |
dc.publisher | Springer, Cham | en |
dc.relation.ispartof | Proceedings of the Second International Conference on Innovations in Computing Research (ICR’23) | en |
dc.relation.ispartofseries | Lecture Notes in Networks and Systems | en |
dc.title | CNN-Based Handwriting Analysis for the Prediction of Autism Spectrum Disorder | en |
dc.type | Conference Publication | en |
dc.relation.conference | The Second International Conference on Innovations in Computing Research (ICR’23) | en |
dc.identifier.doi | 10.1007/978-3-031-35308-6_14 | en |
local.contributor.firstname | Nafisa | en |
local.contributor.firstname | Mohammad Zavid | en |
local.contributor.firstname | Muhammad | en |
local.contributor.firstname | Prabal Datta | en |
local.contributor.firstname | Mia | en |
local.contributor.firstname | Subrata | en |
local.profile.school | School of Law | en |
local.profile.school | School of Science and Technology | en |
local.profile.email | mrahim@une.edu.au | en |
local.profile.email | schakra3@une.edu.au | en |
local.output.category | E1 | en |
local.record.place | au | en |
local.record.institution | University of New England | en |
local.date.conference | 4th - 6th September, 2023 | en |
local.conference.place | Madrid, Spain | en |
local.publisher.place | Switzerland | en |
local.format.startpage | 165 | en |
local.format.endpage | 174 | en |
local.series.issn | 2367-3370 | en |
local.series.issn | 2367-3389 | en |
local.peerreviewed | Yes | en |
local.identifier.volume | 721 | en |
local.contributor.lastname | Nawer | en |
local.contributor.lastname | Parvez | en |
local.contributor.lastname | Iqbal Hossain | en |
local.contributor.lastname | Barua | en |
local.contributor.lastname | Rahim | en |
local.contributor.lastname | Chakraborty | en |
dc.identifier.staff | une-id:mrahim | en |
dc.identifier.staff | une-id:schakra3 | en |
local.profile.orcid | 0000-0003-0637-8445 | en |
local.profile.orcid | 0000-0002-0102-5424 | en |
local.profile.role | author | en |
local.profile.role | author | en |
local.profile.role | author | en |
local.profile.role | author | en |
local.profile.role | author | en |
local.profile.role | author | en |
local.identifier.unepublicationid | une:1959.11/59731 | en |
dc.identifier.academiclevel | Academic | en |
dc.identifier.academiclevel | Academic | en |
dc.identifier.academiclevel | Academic | en |
dc.identifier.academiclevel | Academic | en |
dc.identifier.academiclevel | Academic | en |
dc.identifier.academiclevel | Academic | en |
local.title.maintitle | CNN-Based Handwriting Analysis for the Prediction of Autism Spectrum Disorder | en |
local.output.categorydescription | E1 Refereed Scholarly Conference Publication | en |
local.conference.details | The Second International Conference on Innovations in Computing Research (ICR’23), Madrid, Spain, 4th - 6th September, 2023 | en |
local.search.author | Nawer, Nafisa | en |
local.search.author | Parvez, Mohammad Zavid | en |
local.search.author | Iqbal Hossain, Muhammad | en |
local.search.author | Barua, Prabal Datta | en |
local.search.author | Rahim, Mia | en |
local.search.author | Chakraborty, Subrata | en |
local.open.fileurl | https://rune.une.edu.au/web/retrieve/fae5dd49-2e01-4e1c-94cd-b27c16cf277c | en |
local.uneassociation | Yes | en |
dc.date.presented | 2023-09-04 | - |
local.atsiresearch | No | en |
local.sensitive.cultural | No | en |
local.year.published | 2023 | en |
local.year.presented | 2023 | en |
local.fileurl.open | https://rune.une.edu.au/web/retrieve/fae5dd49-2e01-4e1c-94cd-b27c16cf277c | en |
local.subject.for2020 | 4601 Applied computing | en |
local.date.start | 2023-09-04 | - |
local.date.end | 2023-09-06 | - |
local.profile.affiliationtype | External Affiliation | en |
local.profile.affiliationtype | External Affiliation | en |
local.profile.affiliationtype | External Affiliation | en |
local.profile.affiliationtype | UNE Affiliation | en |
local.profile.affiliationtype | UNE Affiliation | en |
local.profile.affiliationtype | UNE Affiliation | en |
local.date.moved | 2024-06-26 | en |
Appears in Collections: | Conference Publication School of Law School of Science and Technology |
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