Synthesizing Realistic ARMD Fundus Images Using Generative Adversarial Networks (GANs)-Reference-Cited by-同舟云学术

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Synthesizing Realistic ARMD Fundus Images Using Generative Adversarial Networks (GANs)

Published:2023 Issue: Volume: Page:587-599
ISSN:2194-5357
Container-title:Intelligent Computing and Communication
language:
Short-container-title:

Author:

Kalisapudi Sesha Sai Aneeswar,Raj Vavilala Divya^ORCID,Vanam Shubhasri^ORCID,Anne Jasvith Chand

Publisher

Springer Nature Singapore

Link

https://link.springer.com/content/pdf/10.1007/978-981-99-1588-0_51

Reference15 articles.

1. Grzybowski A, Shtayer C, Schwartz SG et al (2021) The 100 most-cited papers on age-related macular degeneration: a bibliographic perspective BMJ Open Ophthalmol 6:e000823. https://doi.org/10.1136/bmjophth-2021-000823

2. https://www.kaggle.com/meaninglesslives/using-resnet50-pretrained-model-inkera

3. https://www.allaboutvision.com/conditions/blurry-vision.html

4. Sandhya M, Morampudi MK, Grandhe R, Kumari R, Banda C, Gonthina N (2022) Detection of diabetic retinopathy (DR) severity from fundus photographs: an ensemble approach using weighted average. Arab J Sci Eng pp 1–8. https://doi.org/10.1007/s13369-021-06381-1

5. https://pubmed.ncbi.nlm.nih.gov/30629091/

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