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Dergiler / Acta Infologica / 2020 / Volume: 4 Issue: 2

Üretken Çekişmeli Ağlar ile Görsel Çözünürlük Artırımı Üzerine Bir Araştırma

A Survey on Image Super-Resolution with Generative Adversarial Networks

Hürkal Hüsem(İSTANBUL ÜNİVERSİTESİ - CERRAHPAŞA, LİSANSÜSTÜ EĞİTİM ENSTİTÜSÜ, BİLGİSAYAR MÜHENDİSLİĞİ (DR))0000-0002-5414-6481
Zeynep Orman(İSTANBUL ÜNİVERSİTESİ - CERRAHPAŞA, MÜHENDİSLİK FAKÜLTESİ, BİLGİSAYAR MÜHENDİSLİĞİ BÖLÜMÜ)0000-0002-0205-4198
Sayfa
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Yayın Tarihi
2020-12-31
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Yapay Zeka Hızlı Bakış & Çıkarımlar

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⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

Üretilen görselin kalitesini ölçen başarım ölçümleri, sinir ağında kullanılan yitim fonksiyonları ve Üretken Çekişmeli Ağ kullanarak tekil-görsel çözünürlük artırımı üzerine çalışılmış araştırma makaleleri bu çalışmanın temel alanında yer almaktadır.

📌 3 Maddede Bu Makale

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Amaç & Hipotez:Çözünürlük artırımı (süper-çözünürlük) belirli bir artırım değeri ile görselin yüksek çözünürlükteki detaylarını korumaya çalışarak boyutlarını artırma işlemidir.
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Temel Bulgular & Veri:Ancak bu konudaki en etkili teknikler çeşitli sinir ağı tasarımlarından yararlanan tekniklerdir.
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Sonuç & Katkı:Üretilen görselin kalitesini ölçen başarım ölçümleri, sinir ağında kullanılan yitim fonksiyonları ve Üretken Çekişmeli Ağ kullanarak tekil-görsel çözünürlük artırımı üzerine çalışılmış araştırma makaleleri bu çalışmanın temel alanında yer almaktadır.
🔬Tür:Review
📍Kapsam:Genişletilmiş Akademik Örneklem
⚙️Değişkenler:Image Super-Resolution · Generative Adversarial Networks · Resolution Enhancement

Özet

Çözünürlük artırımı (süper-çözünürlük) belirli bir artırım değeri ile görselin yüksek çözünürlükteki detaylarını korumaya çalışarak boyutlarını artırma işlemidir. Süper-çözünürlük birçok teknik ile gerçekleştirilebilir. Ancak bu konudaki en etkili teknikler çeşitli sinir ağı tasarımlarından yararlanan tekniklerdir. Bazı ağ tasarımları belirli konularda diğerlerine göre daha uygundur. Bu çalışma Üretken Çekişmeli Ağlar ile gerçekleştirilmiş çözünürlük yükseltme işlemlerine odaklanmıştır. Birçok çalışma yapar veri üretimi ve verinin daha anlamlı hale getirilmesi gibi çeşitli konularda bu yapay sinir ağı tipini kullanır. Bu yapay sinir ağı tipi ile yapay veri üretimi ve verinin daha anlamlı hale getirilmesi gibi alanlarda başarılı çalışmalar mevcuttur. Daha gerçekçi sonuçlar üretebilmesi için birbirini yenmeye çalışan iki alt ağdan oluşması bu ağ türünün kilit noktasıdır. Üretilen görselin kalitesini ölçen başarım ölçümleri, sinir ağında kullanılan yitim fonksiyonları ve Üretken Çekişmeli Ağ kullanarak tekil-görsel çözünürlük artırımı üzerine çalışılmış araştırma makaleleri bu çalışmanın temel alanında yer almaktadır.

Abstract

Super-resolution is a process to increase image dimensions with a specific upscaling factor while trying to preserve details that matche with the original high-resolution form. Super-resolution can be done with many techniques. But the most effective technique is the one that takes advantage of several neural network designs. Some network designs are more appropriate than others on the specific subject. This study focuses on super resolution studies using Generative Adversarial Network. Many studies use this neural network type to look at various topics such as artificial data production and making the data more meaningful. The key point of this neural network type is having two different sub-networks that try to defeat each other in order to make more realistic results. Performance metrics that measure the quality of a generated image, loss functions used in a neural network and research papers on super-resolution with Generative Adversarial Network are the main domains of this study.

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Bu Makaleye Atıf Yap

Hüsem, H., Orman, Z. (2020). Üretken Çekişmeli Ağlar ile Görsel Çözünürlük Artırımı Üzerine Bir Araştırma. Acta Infologica, Volume: 4 Issue: 2. https://doi.org/10.26650/acin.765320

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