Results 101 to 110 of about 134,465 (305)
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 +6 more
wiley +1 more source
A Dual Attentive Generative Adversarial Network for Remote Sensing Image Change Detection [PDF]
, 2023 Luyi Qiu +3 more
openalex +1 more source
A Novel GAN-based Fault Diagnosis Approach for Imbalanced Industrial Time Series
, 2019 This paper proposes a novel fault diagnosis approach based on generative adversarial networks (GAN) for imbalanced industrial time series where normal samples are much larger than failure cases.
Cheng, Cheng +4 more
core
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
Influence Estimation for Generative Adversarial Networks [PDF]
, 2021 Naoyuki Terashita +3 more
openalex
InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets
, 2016 This paper describes InfoGAN, an information-theoretic extension to the Generative Adversarial Network that is able to learn disentangled representations in a completely unsupervised manner. InfoGAN is a generative adversarial network that also maximizes
Abbeel, Pieter +5 more
core
Advanced Intelligent Discovery, EarlyView.Exosomes are emerging as powerful biomarkers for disease diagnosis and monitoring. This review highlights the integration of surface‐enhanced Raman spectroscopy with artificial intelligence to enhance molecular fingerprinting of exosomes. Machine learning and deep learning techniques improve spectral interpretation, enabling accurate classification of ...
Munevver Akdeniz +2 more
wiley +1 more source
Advanced Intelligent Discovery, EarlyView.A novel convolutional neural network architecture enables rapid, unsupervised analysis of IR spectroscopic data from DRIFTS and IRRAS. By combining synthetic data generation with parallel convolutional layers and advanced regularization, the model accurately resolves spectral features of adsorbed CO, offering real‐time insights into ceria surface ...
Mehrdad Jalali +5 more
wiley +1 more source
PCSGAN: Perceptual cyclic-synthesized generative adversarial networks for thermal and NIR to visible image transformation [PDF]
, 2020 Kancharagunta Kishan Babu +1 more
openalex +1 more source
Advanced Intelligent Discovery, EarlyView.CrossMatAgent is a multi‐agent framework that combines large language models and diffusion‐based generative AI to automate metamaterial design. By coordinating task‐specific agents—such as describer, architect, and builder—it transforms user‐provided image prompts into high‐fidelity, printable lattice patterns.
Jie Tian +12 more
wiley +1 more source