Derin Öğrenme ve Destek Vektör Makineleri İle Görüntüden Cinsiyet Tahmini

Yıl 2020, Cilt: 8 Sayı: 3, 2208 - 2228, 31.07.2020

Sedat Metlek , Kiyas Kayaalp

https://doi.org/10.29130/dubited.707316

Cited By: 9

Öz

Yapılan çalışmada günümüzün popular konularından olan derin öğrenme algoritmaları üzerine bir uygulama geliştirilmiştir. Geliştirilen uygulamada görüntülerden yüz tespiti yapılıp ardından görüntüdeki kişinin cinsiyet tahmini yapılmıştır. Bu uygulamada Wiki görüntü veri tabanından elde edilen 62328 görüntü kullanılmıştır. Kullanılan görüntüler üzerinde, yüz görüntüsü bulunmayanlar veri setinden çıkartılarak yeni bir veri oluşturulmuştur. Oluşturulan veri setindeki görüntülerden, ileri derin öğrenme tekniklerinden biri olan Evrişimsel Sinir Ağları yöntemi kullanılarak öznitelikler çıkartılmıştır. Elde edilen özniteliklerde Destek Vektör Makinesi (DVM) ile sınıflandırılmıştır. Sınıflandırma başarı sonucu karmaşıklık matrisi ile gösterilmiş olup, %94,4 başarı oranı ile sınıflandırma işlemi gerçekleştirilmiştir.

Anahtar Kelimeler

Derin öğrenme, , Evrişimsel sinir ağı, , Görüntüden cinsiyet tahmini

Kaynakça

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