Improved Generative Convolution Method for Image Generation-Reference-Cited by-同舟云学术

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Improved Generative Convolution Method for Image Generation

Published:2022-10-19 Issue: Volume: Page:
ISSN:
Container-title:2022 13th International Conference on Information and Communication Technology Convergence (ICTC)
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Author:

Park Seung¹,Yang Min-Uk²,Kim Geun-Hyeong²,Im Jueng-Eun²,Kim Ki-Hun²,Shin Yong-Goo³

Affiliation:

1. Biomedical Engineering, Chungbuk National University Hospital,Chungcheongbuk-do,Rep. of Korea

2. Medical AI Research Team, Chungbuk National University Hospital,Chungcheongbuk-do,Rep. of Korea

3. Hannam University,Department of Artificial Intelligence,Daejeon,Rep. of Korea

Funder

Korea Health Industry Development Institute (KHIDI)

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9952188/9952355/09952596.pdf?arnumber=9952596

Reference41 articles.

1. Large scale gan training for high fidelity natural image synthesis;brock;ArXiv Preprint,2018

2. Conditional Convolution Projecting Latent Vectors on Condition-Specific Space

3. PConv: simple yet effective convolutional layer for generative adversarial network

4. A novel generator with auxiliary branch for improving gan performance;park;ArXiv Preprint,2021

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Effective shortcut technique for generative adversarial networks;Applied Intelligence;2022-05-05

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