GAN (Generative Adversarial Network)-Based Image Super-Resolution: A Technical Perspective-Reference-Cited by-同舟云学术

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GAN (Generative Adversarial Network)-Based Image Super-Resolution: A Technical Perspective

Published:2023 Issue: Volume: Page:283-293
ISSN:2367-3370
Container-title:IOT with Smart Systems
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Author:

Yadav Hemant,Vasa Jalpesh^ORCID,Patel Rudra

Publisher

Springer Nature Singapore

Link

https://link.springer.com/content/pdf/10.1007/978-981-99-3761-5_27

Reference30 articles.

1. Gyu HJ et al (2023) Efficient fingerprint-map generating method for IEEE 802.11 indoor positioning using SRGAN. In: Proceedings of the 2023 International Technical Meeting of The Institute of Navigation

2. Ioffe S, Szegedy C (2015) Batch normalization: accelerating deep network training by reducing internal covariate shift. In: International conference on machine learning. PMLR (2015)

3. Sharma A, Shrivastava BP (2022) Different techniques of image SR using deep learning: a review. IEEE Sens J 23(3):1724–1733

4. Borji A (2022) Pros and cons of GAN evaluation measures: New developments. Comput Vis Image Underst 215:103329

5. GAN—ways to improve GAN performance (https://towardsdatascience.com/gan-ways-to-improve-gan-performance-acf37f9f59b)

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