YAPAY ZEKÂ VE RESİM KESİŞİMİNDE ALGORİTMALAR, TEKNİKLER VE TESPİT YÖNTEMLERİ

Year 2025, Volume: 8 Issue: 1, 25 - 39, 26.08.2025

Mehmet Akif Özdal

https://doi.org/10.56809/icujtas.1523272

Abstract

Bu araştırma, yapay zekânın resim üzerindeki etkilerini algoritmalar, teknikler ve tespit yöntemleri kapsamında incelemektedir. Araştırmada, derin öğrenme ve generative adversarial networks (GAN) algoritmalarının resimsel stilleri, kompozisyonları ve renk paletlerini öğrenme ve yeni sanatsal formlar oluşturma yeteneği ile yapay zekâ (YZ) tarafından oluşturulan resimlerin tespitinde kullanılan yedi araç ve on adet yöntem incelenmiştir.
Bu kapsamda, alan yazın taramasıyla toplanan veriler, nitel araştırma yöntemlerinden karşılaştırmalı analiz ve mantıksal akıl yürütme yöntemleri kullanılarak yorumlanmış ve incelenen literatür ile sınırlandırılmıştır.
Bulgular, yapay sinir ağları ve derin öğrenme yöntemlerinin resimsel üretim ve analizde kritik rol oynadığını, görsel analiz yöntemlerinin ise dijital resimlerin detaylı incelenmesine olanak sağladığını göstermiştir. Sonuçlar ise bulgulara bağlı kalarak, YZ ve resim kesişiminde kullanılan algoritmaların üretim ve değerlendirme süreçlerinde önemli dönüşümler yarattığını ortaya koymuştur.

Keywords

Yapay Zekâ , Algoritma , Derin öğrenme , Resim , Görsel analiz

ALGORITHMS, TECHNIQUES AND DETECTION METHODS IN ARTIFICIAL INTELLIGENCE AND IMAGE INTERSECTION

Abstract

This research examines the effects of artificial intelligence on painting within the scope of algorithms, techniques and detection methods. In the research, seven tools and ten methods used in the detection of paintings created by artificial intelligence (AI) were examined, with the ability of deep learning and generative adversarial networks (GAN) algorithms to learn pictorial styles, compositions and color palettes and create new artistic forms. In this context, the data collected through literature review were interpreted using comparative analysis and logical reasoning methods, which are among the qualitative research methods, and were limited to the literature examined. Findings have shown that artificial neural networks and deep learning methods play a critical role in pictorial production and analysis, while visual analysis methods allow detailed examination of digital images. The results, adhering to the findings, revealed that the algorithms used at the intersection of AI and image created significant transformations in the production and evaluation processes.

Keywords

Artificial Intelligence , Algorithm , Deep learning , Image , Visual analysis

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