Results 31 to 40 of about 215,845 (322)

Morphology Control of One-Dimensional gallium nitride Nanostructures by Modulating the Crystallinity of Sacrificial gallium oxide Templates [PDF]

Archives of Metallurgy and Materials, 2021
In this study, we demonstrated a method of controllably synthesizing one-dimensional nanostructures having a dense or a hollow structure using fibrous sacrificial templates with tunable crystallinity.
Yun Taek Ko, Mijeong Park, Jingyeong Park, Jaeyun Moon, Yong-Ho Choa, Young-In Lee   +5 more
doaj   +1 more source

Wasserstein Proximal of GANs [PDF]

, 2021
We introduce a new method for training generative adversarial networks by applying the Wasserstein-2 metric proximal on the generators. The approach is based on Wasserstein information geometry. It defines a parametrization invariant natural gradient by pulling back optimal transport structures from probability space to parameter space.
Guido Montúfar, Guido Montúfar, Alex Tong Lin, Wuchen Li, Stanley Osher   +4 more
openaire   +3 more sources

Study of semi-polar gallium nitride grown on m-sapphire by chloride vapor-phase epitaxy

Конденсированные среды и межфазные границы, 2023
In this study, we analyzed the result of the influence of the non-polar plane of a sapphire substrate on the structural, morphological, and optical properties and Raman scattering of the grown epitaxial GaN film.
Pavel V. Seredin, Nikolay A. Kurilo, Obaid Radam Ali, Nikita S. Buylov, Dmitry L. Goloshchapov, Sergey Alexandrovich Ivkov, Alexandr S. Lenshin, Ivan N. Arsentyev, Alexey V. Nashchekin, Shukrilo Sh. Sharofidinov, Andrey M. Mizerov, Maksim S. Sobolev, Evgeniy V. Pirogov, Igor V. Semeykin   +13 more
doaj   +1 more source

Breakthrough Solution for Antimicrobial Resistance Detection: Surface‐Enhanced Raman Spectroscopy‐based on Artificial Intelligence

Advanced Materials Interfaces, EarlyView., 2023
This review discusses the use of Surface‐Enhanced Raman Spectroscopy (SERS) combined with Artificial Intelligence (AI) for detecting antimicrobial resistance (AMR). Various SERS studies used with AI techniques, including machine learning and deep learning, are analyzed for their advantages and limitations.
Zakarya Al‐Shaebi, Munevver Akdeniz, Awel Olsido Ahmed, Mine Altunbek, Omer Aydin   +4 more
wiley   +1 more source

Generative Adversarial Networks and Adversarial Autoencoders: Tutorial and Survey [PDF]

arXiv, 2021
This is a tutorial and survey paper on Generative Adversarial Network (GAN), adversarial autoencoders, and their variants. We start with explaining adversarial learning and the vanilla GAN. Then, we explain the conditional GAN and DCGAN. The mode collapse problem is introduced and various methods, including minibatch GAN, unrolled GAN, BourGAN, mixture
arxiv  

Magnetotransport study on AlInN/(GaN)/AlN/GaN heterostructures [PDF]

physica status solidi (a), 2012
AbstractWe report the effect of a thin GaN (2 nm) interlayer on the magnetotransport properties of AlInN/AlN/GaN‐based heterostructures. Two samples were prepared (Sample A: AlInN/AlN/GaN and sample B: AlInN/GaN/AlN/GaN). Van der Pauw and Hall measurements were performed in the 1.9–300 K temperature range. While the Hall mobilities were similar at room
Bayrakli, A., Arslan, E., Firat, T., Ozcan, S., Kazar, O., Cakmak, H., Ozbay, E.   +6 more
openaire   +6 more sources

Подтверждение методом картирования тока, наведенного электронным пучком, самопроизвольного легирования GaN нитевидных нанокристаллов из вицинальной подложки SiC/Si

Конденсированные среды и межфазные границы, 2023
Данная работа посвящена подтверждению спонтанного легирования GaN нитевидных нанокристаллов, выращенных на вицинальных гибридных подложках SiC/Si, методом картирования тока, наведенного электронным пучком.
Родион Романович Резник, Владислав Олегович Гридчин, Константин Павлович Котляр, Владимир Владимирович Неплох, Андрей Викторович Осипов, Сергей Арсеньевич Кукушкин, Omar Saket, Maria Tchernycheva, Георгий Эрнстович Цырлин   +8 more
doaj   +1 more source

Sequential training of GANs against GAN-classifiers reveals correlated "knowledge gaps" present among independently trained GAN instances [PDF]

arXiv, 2023
Modern Generative Adversarial Networks (GANs) generate realistic images remarkably well. Previous work has demonstrated the feasibility of "GAN-classifiers" that are distinct from the co-trained discriminator, and operate on images generated from a frozen GAN.
arxiv  

Growth condition dependence of unintentional oxygen incorporation in epitaxial GaN

Science and Technology of Advanced Materials, 2016
Growth conditions have a tremendous impact on the unintentional background impurity concentration in gallium nitride (GaN) synthesized by molecular beam epitaxy and its resulting chemical and physical properties.
Felix Schubert, Steffen Wirth, Friederike Zimmermann, Johannes Heitmann, Thomas Mikolajick, Stefan Schmult   +5 more
doaj   +1 more source

Tampered and Computer-Generated Face Images Identification Based on Deep Learning

Applied Sciences, 2020
Image forgery is an active topic in digital image tampering that is performed by moving a region from one image into another image, combining two images to form one image, or retouching an image.
L. Minh Dang, Kyungbok Min, Sujin Lee, Dongil Han, Hyeonjoon Moon   +4 more
doaj   +1 more source