Autism Detection using Visual and Behavioral Data

Sadaf, Nafisa; Shaer, Karishma; Momin, Farhan M Nafis

dc.contributor.author	Sadaf, Nafisa
dc.contributor.author	Shaer, Karishma
dc.contributor.author	Momin, Farhan M Nafis
dc.date.accessioned	2022-04-16T16:02:18Z
dc.date.available	2022-04-16T16:02:18Z
dc.date.issued	2021-03-30
dc.identifier.uri	http://hdl.handle.net/123456789/1327
dc.description	Supervised by Mr. Hasan Mahmud, Assistant Professor, Department of Computer Science and Engineering(CSE), Islamic University of Technology(IUT), Board Bazar, Gazipur-1704, Bangladesh	en_US
dc.description.abstract	Diagnosing Autism Spectrum Disorder (ASD) can be difficult as there is no existing medical test for detecting Autism. The only clinical method for diagnosing ASD are standardized tests which require prolonged diagnostic time and can be expensive. Autism diagnosis can be formulated as a typical machine learning classification problem between ASD patients and a control group, which requires large datasets with different modalities to be trained on, in order to yield accurate results. However, the unavailability of such robust datasets stands as a threat to this automated diagnosis. To resolve this, we propose a method of Autism Detection using Visual and Behavioral Data. The proposed technique first relates the two datasets by generating	en_US
dc.language.iso	en	en_US
dc.publisher	Department of Computer Science and Engineering(CSE), Islamic University of Technology(IUT), Board Bazar, Gazipur, Bangladesh	en_US
dc.title	Autism Detection using Visual and Behavioral Data	en_US
dc.type	Thesis	en_US