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All Journal JOURNAL OF INFORMATICS AND COMPUTER SCIENCE JOIV : International Journal on Informatics Visualization JOURNAL OF INFORMATICS AND COMPUTER SCIENCE Jurnal Teknologi Terapan and Sains 4.0 INJURITY: Journal of Interdisciplinary Studies Jurnal INFOTEL J-SIGN (Journal Of Informatics, Information System, And Artificial Intelligence) DCS: Jurnal Pengabdian Masyarakat
Junidar, Junidar
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Agriculture, Biological Sciences & Forestry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Public Health Social Sciences

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Journal : JOIV : International Journal on Informatics Visualization

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Comparative Analysis of Homomorphic and Morphological Filters Using Inception V3 for Thermal Facial Image Classification of Autistic Children Catur Andryani, Nur Afny; Melinda, Melinda; Tariliani, Cut Dara; Oktiana, Maulisa; Junidar, Junidar
JOIV : International Journal on Informatics Visualization Vol 9, No 3 (2025)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.9.3.2885

Abstract

Autism Spectrum Disorder (ASD) is a neuro-developmental disorder characterized by varying degrees of difficulty in social interaction and communication and repetitive behaviors. Early confirmation of the diagnosis of ASD leads to early appropriate treatment. However, confirming ASD diagnosis is challenging due to its wide spectrum and challenging behavior assessment. This research proposes a technology-based ASD diagnosis on children utilizing thermal facial analysis. This is conducted subject to the uniqueness of facial expression that is typically applied to children with ASD. A modified Inception V3 architecture did the intended thermal facial analysis for ASD diagnosis. Homomorphic filters and morphological filters are applied to the data pre-processing to improve the classification ability. The proposed identification method shows better sensitivity to the false-positive aspect. It is indicated by better performance in terms of precision, with a rate of 90% to 91%. This research is expected to support medical experts in confirming early diagnosis in children with ASD.
Co-Authors Afdhal Afdhal Aqif, Hurriyatul Binti Basir, Nurlida Catur Andryani, Nur Afny Jummi, Cut Vita Rajiatul Juwita Juwita, Juwita Melinda Melinda Mutiawani, Viska Nargaza, Juanda Nurdin, Zahnur Nurul Hamdi Oktiana, Maulisa Rajiatul Jummi, Cut Vita S, Kikye Martiwi Sahila, Herma Miftahul Serianti, Putri sukiakhy, kikye martiwi Syifa, Dian Tariliani, Cut Dara Umam, Teuku Khairul Zainal, Zulfan Zainuddin, Zul Ikram