Görüntü Kazıma Yoluyla Oluşturulan Örnek Veri Kümesinin Evrişimsel Sinir Ağı Tabanlı Görüntü Sınıflama Üzerine Etkisinin İncelenmesi

Yıl 2023, Cilt: 11 Sayı: 3, 1388 - 1398, 31.07.2023

Tolga Hayıt

https://doi.org/10.29130/dubited.1120967

Cited By: 1

Öz

Derin öğrenme tabanlı görüntü sınıflandırma çalışmalarının en önemli aşamalarından biri veri elde etme aşamasıdır. Modeli eğitecek veri setinin göreve özgü ve uygun kalitede olması gerekmektedir. Bu nedenle veri setinin oluşturulma süreci araştırmacılar için zahmetli ve yorucu bir süreç olabilmektedir. Web kazıma teknikleri çalışmalarda kullanılabilecek uygun veri setlerinin oluşturulmasında araştırmacılara çözümler sunmaktadır. Özellikle derin öğrenme gibi çok sayıda veri ihtiyacı bulunan görevlerde bu tekniklerin kullanılması süreci ciddi anlamda hızlandırabilmektedir. Bu bağlamda bu çalışma, örnek bir görüntü sınıflandırma görevi için görsel kazıma teknolojisi ile oluşturulan veri setinin sınıflandırmaya başarısını araştırmaktadır. Çalışmada farklı CNN modelleri kullanılarak, oluşturulan örnek veri seti eğitilmiştir. Doğruluk ve diğer performans ölçütleri görsel kazıma yoluyla elde edilen veri setinin görüntü sınıflandırma görevleri için kullanılabileceğini desteklemektedir.

Anahtar Kelimeler

Görsel kazıma, Web kazıma, Evrişimsel Sinir Ağı, Derin Öğrenme, Görüntü sınıflandırma

Kaynakça

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