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Akademický článek

Realistic High-Resolution Body Computed Tomography Image Synthesis by Using Progressive Growing Generative Adversarial Network: Visual Turing Test

Autor: Park, Ho Young, Bae, Hyun-Jin, Hong, Gil-Sun, Kim, Minjee, Yun, JiHye, Park, Sungwon, Chung, Won Jung, Kim, NamKug

Publikováno v: JMIR Medical Informatics, Vol 9, Iss 3, p e23328 (2021)

BackgroundGenerative adversarial network (GAN)–based synthetic images can be viable solutions to current supervised deep learning challenges. However, generating highly realistic images is a prerequisite for these approaches. ObjectiveThe aim of t

Externí odkaz: https://doaj.org/article/4b7fb07c0283439a8de1276621792fa5

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Machine Learning Assisted Design and Optimization of Transition Metal-Incorporated Carbon Quantum Dot Catalysts for Hydrogen Evolution Reaction

Autor: Nguyen, Duong Nguyen, Kim, Min-Cheol, Baeck, Unbeom, Lim, Jaehyoung, Shin, Namsoo, Kim, Jaekook, Choi, Heechae, Park, Ho Seok, Sim, Uk, Kim, Jung Kyu

Development of cost-effective hydrogen evolution reaction (HER) catalysts with outstanding catalytic activity, replacing cost-prohibitive noble metal-based catalysts, is critical for practical green hydrogen production. A popular strategy for promoti

Externí odkaz: http://arxiv.org/abs/2210.14701