Acta Infologica

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DOI :10.26650/acin.765320   IUP :10.26650/acin.765320    Tam Metin (PDF)

Üretken Çekişmeli Ağlar ile Görsel Çözünürlük Artırımı Üzerine Bir Araştırma

Hürkal Hüsem, Zeynep Orman

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. 

Anahtar Kelimeler: Image Super-Resolution, Generative Adversarial Networks, Resolution Enhancement
DOI :10.26650/acin.765320   IUP :10.26650/acin.765320    Tam Metin (PDF)

A Survey on Image Super-Resolution with Generative Adversarial Networks

Hürkal Hüsem, Zeynep Orman

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. 

Anahtar Kelimeler: Image Super-Resolution, Generative Adversarial Networks, Resolution Enhancement

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DIŞA AKTAR



APA

Hüsem, H., & Orman, Z. (2020). Üretken Çekişmeli Ağlar ile Görsel Çözünürlük Artırımı Üzerine Bir Araştırma. Acta Infologica, 4(2), 139-154. https://doi.org/10.26650/acin.765320


AMA

Hüsem H, Orman Z. Üretken Çekişmeli Ağlar ile Görsel Çözünürlük Artırımı Üzerine Bir Araştırma. Acta Infologica. 2020;4(2):139-154. https://doi.org/10.26650/acin.765320


ABNT

Hüsem, H.; Orman, Z. Üretken Çekişmeli Ağlar ile Görsel Çözünürlük Artırımı Üzerine Bir Araştırma. Acta Infologica, [Publisher Location], v. 4, n. 2, p. 139-154, 2020.


Chicago: Author-Date Style

Hüsem, Hürkal, and Zeynep Orman. 2020. “Üretken Çekişmeli Ağlar ile Görsel Çözünürlük Artırımı Üzerine Bir Araştırma.” Acta Infologica 4, no. 2: 139-154. https://doi.org/10.26650/acin.765320


Chicago: Humanities Style

Hüsem, Hürkal, and Zeynep Orman. “Üretken Çekişmeli Ağlar ile Görsel Çözünürlük Artırımı Üzerine Bir Araştırma.” Acta Infologica 4, no. 2 (May. 2024): 139-154. https://doi.org/10.26650/acin.765320


Harvard: Australian Style

Hüsem, H & Orman, Z 2020, 'Üretken Çekişmeli Ağlar ile Görsel Çözünürlük Artırımı Üzerine Bir Araştırma', Acta Infologica, vol. 4, no. 2, pp. 139-154, viewed 4 May. 2024, https://doi.org/10.26650/acin.765320


Harvard: Author-Date Style

Hüsem, H. and Orman, Z. (2020) ‘Üretken Çekişmeli Ağlar ile Görsel Çözünürlük Artırımı Üzerine Bir Araştırma’, Acta Infologica, 4(2), pp. 139-154. https://doi.org/10.26650/acin.765320 (4 May. 2024).


MLA

Hüsem, Hürkal, and Zeynep Orman. “Üretken Çekişmeli Ağlar ile Görsel Çözünürlük Artırımı Üzerine Bir Araştırma.” Acta Infologica, vol. 4, no. 2, 2020, pp. 139-154. [Database Container], https://doi.org/10.26650/acin.765320


Vancouver

Hüsem H, Orman Z. Üretken Çekişmeli Ağlar ile Görsel Çözünürlük Artırımı Üzerine Bir Araştırma. Acta Infologica [Internet]. 4 May. 2024 [cited 4 May. 2024];4(2):139-154. Available from: https://doi.org/10.26650/acin.765320 doi: 10.26650/acin.765320


ISNAD

Hüsem, Hürkal - Orman, Zeynep. “Üretken Çekişmeli Ağlar ile Görsel Çözünürlük Artırımı Üzerine Bir Araştırma”. Acta Infologica 4/2 (May. 2024): 139-154. https://doi.org/10.26650/acin.765320



ZAMAN ÇİZELGESİ


Gönderim07.07.2020
Kabul17.08.2020
Çevrimiçi Yayınlanma31.12.2020

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İstanbul Üniversitesi Yayınları, uluslararası yayıncılık standartları ve etiğine uygun olarak, yüksek kalitede bilimsel dergi ve kitapların yayınlanmasıyla giderek artan bilimsel bilginin yayılmasına katkıda bulunmayı amaçlamaktadır. İstanbul Üniversitesi Yayınları açık erişimli, ticari olmayan, bilimsel yayıncılığı takip etmektedir.