Results 131 to 140 of about 124,232 (320)

Regional attention generative adversarial network

Electronics Letters, 2019
In this Letter, the authors propose a novel attention mechanism combined with a classical generative adversarial network (GAN) model to improve the visual quality of generated samples. This novel attention model is named regional attention GAN.
Wei Wang, Haifeng Hu, Yi Huang, Chongchong Ruan, Dihu Chen   +4 more
doaj   +1 more source

Statistical parametric speech synthesis using generative adversarial networks under a multi-task learning framework [PDF]

, 2017
Shan Yang, Lei Xie, Xiao Dong Chen, Xiaoyan Lou, Xuan Zhu, Dongyan Huang, Haizhou Li   +6 more
openalex   +1 more source

Digital Twin of Solid Oxide Electrochemical Cells: From 3D Microstructure Reconstruction to Multiphysics Modeling

Advanced Energy Materials, EarlyView.
This review outlines the implementation of digital twin frameworks for solid oxide electrochemical cells (SOCs), encompassing 3D microstructure reconstruction, quantitative morphological analysis, and microstructure‐resolved multiphysics modeling. Emphasis is placed on recent advances that position digital twins as powerful tools for microstructure ...
Seungsoo Jang, Yejin Kang, Kyung Taek Bae, Seong Hyun Park, Young Je Park, Dongyeon Kim, Hyeongmin Yu, Hyunjin Kim, Siwon Yu, Kang Taek Lee   +9 more
wiley   +1 more source

Progress of Aqueous Rechargeable Zn–CO2 Batteries with a Focus on Cathode Bifunctional Catalysts

Advanced Energy and Sustainability Research, EarlyView.
Aqueous rechargeable Zn–CO2 batteries are emerging as a promising technology for sustainable energy storage and carbon dioxide (CO2) utilization, owing to their high safety, theoretical capacity, and product diversity. Despite their significant theoretical potential, the application of Zn–CO2 batteries is hindered due to several challenges, including ...
Peng Chen, Xintao Ma, Qingshun Nian, Chunyi Zhi   +3 more
wiley   +1 more source

Domain‐Aware Implicit Network for Arbitrary‐Scale Remote Sensing Image Super‐Resolution

Advanced Intelligent Discovery, EarlyView.
Although existing arbitrary‐scale image super‐resolution methods are flexible to reconstruct images with arbitrary scales, the characteristic of training distribution is neglected that there exists domain shift between samples of various scales. In this work, a Domain‐Aware Implicit Network (DAIN) is proposed to handle it from the perspective of domain
Xiaoxuan Ren, Qian Jiang, Xin Jin, Puming Wang, Xing Chu, Shaowen Yao, Shengfa Miao   +6 more
wiley   +1 more source

Machine‐Learning‐Based, Feature‐Rich Prediction of Alumina Microstructure from Hardness

Advanced Intelligent Discovery, EarlyView.
Herein, high‐performance generative adversarial network (GAN), named ‘Microstructure‐GAN’, is demonstrated. After training, the high‐fidelity, feature‐rich micrographs can be predicted for an arbitrary target hardness. Microstructure details such as small pores and grain boundaries can be observed at the nanometer scale in the predicted 1000 ...
Xiao Geng, Jianan Tang, Ningxuan Wen, Jason Shaw, Siddhartha Sarkar, Lionel Vargas‐Gonzalez, Nicholas Ku, Jianhua Tong, Rajendra K. Bordia, Dongsheng Li, Fei Peng   +10 more
wiley   +1 more source

Face aging with conditional generative adversarial networks [PDF]

, 2017
Grigory Antipov, Moez Baccouche, Jean‐Luc Dugelay   +2 more
openalex   +1 more source

AI‐Enhanced Surface‐Enhanced Raman Scattering for Accurate and Sensitive Biomedical Sensing

Advanced Intelligent Discovery, EarlyView.
AI‐SERS advances spectral interpretation with greater precision and speed, enhancing molecular detection, biomedical analysis, and imaging. This review explores its essential contributions to biofluid analysis, disease identification, therapeutic agent evaluation, and high‐resolution biomedical imaging, aiding diagnostic decision‐making.
Seungki Lee, Rowoon Park, Ho Sang Jung
wiley   +1 more source

What to Make and How to Make It: Combining Machine Learning and Statistical Learning to Design New Materials

Advanced Intelligent Discovery, EarlyView.
Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley   +1 more source

Transfer learning enabled transformer-based generative adversarial networks for modeling and generating terahertz channels

Communications Engineering
Terahertz communications are envisioned as a promising technology for the sixth generation and beyond wireless systems, which can support wireless links with Terabits-per-second (Tbps) data rates.
Zhengdong Hu, Yuanbo Li, Chong Han
doaj   +1 more source