Swin Tabanlı Dönüştürülmüş Görüntülerin Sınıflandırılması

Görüntü sınıflandırma bilgisayarlı görü alanındaki temel çalışmalardan biridir. Görüntü çözünürlüğü ve görüntünün netliği sınıflandırma performansını önemli ölçüde etkileyen faktörlerdendir. Bu çalışmada görüntülerin çözünürlüğünün ve netliğinin Swin tabanlı dönüştürücü olan Swin2SR algoritması kullanılarak artırılmasıyla görüntü sınıflandırma performansı incelenmiştir. Sınıflandırma için transfer öğrenme olarak ResNet18 modeli kullanılmıştır. CIFAR10 veri kümesi üzerinde 50 epok için yapılan deneyler sonucunda Swin2SR algoritmasının görüntülerin çözünürlüğünü ve netliğini artırarak sınıflandırma doğruluğunu %85’ten %87’ye çıkardığı gözlemlenmiştir.

Anahtar Kelimeler:

Görüntü Sınıflandırma, Swin2SR Dönüştürme, Transfer Öğrenme

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