DIAGNOSIS OF AUTISM SPECTRUM DISORDER USING CONVOLUTIONAL NEURAL NETWORKS / (Kayıt no. 292381)
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| 000 -BAŞLIK | |
|---|---|
| Sabit Uzunluktaki Kontrol Alanı | 02883nam a22002777a 4500 |
| 003 - KONTROL NUMARASI KİMLİĞİ | |
| Kontrol Alanı | KOHA |
| 005 - EN SON İŞLEM TARİHİ ve ZAMANI | |
| Kontrol Alanı | 20240228102811.0 |
| 008 - SABİT UZUNLUKTAKİ VERİ ÖGELERİ - GENEL BİLGİ | |
| Sabit Alan | 240228d2023 cy ||||| m||| 00| 0 eng d |
| 040 ## - KATALOGLAMA KAYNAĞI | |
| Özgün Kataloglama Kurumu | CY-NiCIU |
| Kataloglama Dili | eng |
| Çeviri Kurumu | CY-NiCIU |
| Açıklama Kuralları | rda |
| 041 ## - DİL KODU | |
| Metin ya da ses kaydının dil kodu | eng |
| 090 ## - Yerel Tasnif No | |
| tasnif no | D 414 |
| Cutter no | H46 2023 |
| 100 1# - KİŞİ ADI | |
| Yazar Adı (Kişi adı) | Hendr, Amna |
| 245 10 - ESER ADI BİLDİRİMİ | |
| Başlık | DIAGNOSIS OF AUTISM SPECTRUM DISORDER USING CONVOLUTIONAL NEURAL NETWORKS / |
| Sorumluluk Bildirimi | AMNA HENDR; SUPERVISOR: ASSOC. PROF. DR. UMAR ÖZGÜNALP, CO-SUPERVISOR: ASST. PROF. DR. MERYEM ERBİLEK |
| 264 ## - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE | |
| Date of production, publication, distribution, manufacture, or copyright notice | 2023 |
| 300 ## - FİZİKSEL TANIMLAMA | |
| Sayfa, Cilt vb. | xi, 111 sheets; |
| Boyutları | 30 cm. |
| Birlikteki Materyal | 1 CD ROM |
| 336 ## - CONTENT TYPE | |
| Source | rdacontent |
| Content type term | text |
| Content type code | txt |
| 337 ## - MEDIA TYPE | |
| Source | rdamedia |
| Media type term | unmediated |
| Media type code | n |
| 338 ## - CARRIER TYPE | |
| Source | rdacarrier |
| Carrier type term | volume |
| Carrier type code | nc |
| 502 ## - TEZ NOTU | |
| Tez Notu | Thesis (PhD) - Cyprus International University. Institute of Graduate Studies and Research Management Information Systems Department |
| 504 ## - BİBLİYOGRAFİ NOTU | |
| Bibliyografi Notu | Includes References (sheets 96-110) |
| 520 ## - ÖZET NOTU | |
| Özet notu | ABSTRACT <br/>Autism spectrum disorder has been a condition which affects people for a very long period of time. One key point, which still poses a serious challenge is the early diagnosis of the disorder. Early diagnosis of the disease is crucial since the early intervention significantly improves the outcome. The diagnosis of autism spectrum disorder poses a challenge, since it appears in wide variety of ways in subjects. In the literature it is shown that the children with ASD show worse quality of forming letters. Thus, in this thesis, machine learning based, automated ASD diagnosis method has been developed using handwriting as input. In this approach, several different tasks are given to pupils such as drawing rectangles and these drawings are fed into CNN to diagnose ASD. Best to our knowledge, there is no dataset available for this task. Thus, first, a dataset has been formed, where some drawing tasks are given to pupils with ASD and without ASD. Since it is difficult to collect data from pupils with ASD, transfer learning has been employed to increase accuracy. Also, <br/>for each task a different network trained and classification results for the same pupil are combined by taking median of estimated classes (majority voting) by the networks. This has been done since in practice a pupil with ASD might not be willing to finish the task and thus, the input size may vary. Consequently, a dataset <br/>with 104 pupils (split as 80% for training and 20% for testing) is formed and it is shown that the proposed approach can correctly classify ASD with an accuracy of 90.48%, where sensitivity, and specificity are calculated as 80%, and 100% respectively.<br/>Keywords: Autism Detection, Autism Spectrum Disorder, Computer Vision, Convolutional Neural Network, Googlenet, Transfer Learning. |
| 650 #0 - KONU BAŞLIĞI EK GİRİŞ - KONU TERİMİ | |
| Konusal terim veya coğrafi ad | Management Information Systems |
| Alt başlık biçimi | Dissertations, Academic |
| 700 1# - EK GİRİŞ - KİŞİ ADI | |
| Yazar Adı (Kişi adı) | Özgünalp, Umar |
| İlişkili Terim | supervisor |
| 700 1# - EK GİRİŞ - KİŞİ ADI | |
| Yazar Adı (Kişi adı) | Erbilek, Meryem |
| İlişkili Terim | supervisor |
| 942 ## - EK GİRİŞ ÖGELERİ (KOHA) | |
| Sınıflama Kaynağı | Dewey Onlu Sınıflama Sistemi |
| Materyal Türü | Thesis |
| Geri Çekilme Durumu | Kayıp Durumu | Sınıflandırma Kaynağı | Kredi için değil | Koleksiyon Kodu | Kalıcı Konum | Mevcut Konum | Raf Yeri | Kayıt Tarih | Source of acquisition | Toplam Ödünçverme | Yer Numarası | Demirbaş Numarası | Son Görülme Tarihi | Fatura Tarihi | Materyal Türü | Genel / Bağış Notu |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Dewey Onlu Sınıflama Sistemi | Tez Koleksiyonu | CIU LIBRARY | CIU LIBRARY | Depo | 28.02.2024 | Bağış | D 414 H46 2023 | T3728 | 28.02.2024 | 28.02.2024 | Thesis | Management Information Systems Department | ||||
| Dewey Onlu Sınıflama Sistemi | Tez Koleksiyonu | CIU LIBRARY | CIU LIBRARY | Görsel İşitsel | 28.02.2024 | Bağış | D 414 H46 2023 | CDT3728 | 28.02.2024 | 28.02.2024 | Suppl. CD | Management Information Systems Department |