Results 131 to 140 of about 39,370 (305)
Multi-Source Medical Image Fusion Based on Wasserstein Generative Adversarial Networks
IEEE Access, 2019 In this paper, we propose the medical Wasserstein generative adversarial networks (MWGAN), an end-to-end model, for fusing magnetic resonance imaging (MRI) and positron emission tomography (PET) medical images.
Zhiguang Yang +4 more
doaj +1 more source
Large Language Model in Materials Science: Roles, Challenges, and Strategic Outlook
Advanced Intelligent Discovery, EarlyView.Large language models (LLMs) are reshaping materials science. Acting as Oracle, Surrogate, Quant, and Arbiter, they now extract knowledge, predict properties, gauge risk, and steer decisions within a traceable loop. Overcoming data heterogeneity, hallucinations, and poor interpretability demands domain‐adapted models, cross‐modal data standards, and ...
Jinglan Zhang +4 more
wiley +1 more source
A Novel Electromagnetic Sensing Generative Adversarial Network for Uniaxial Objects
Electromagnetic imaging achieves enhanced resolution by leveraging the advanced sensing and data analysis capabilities of Internet of Things (IoT) systems.
Chiu, Chien-Ching;Chen, Po-Hsiang;Jiang, Hao;Shi, Bo-Yu
core +1 more source
Deep learning: Generative adversarial networks and adversarial methods
, 2019 Generative adversarial networks (GANs) and other adversarial methods are based on a game-theoretical perspective on joint optimization of two neural networks as players in a game.
Wolterink, Jelmer M. +7 more
core +1 more source
Advanced Intelligent Discovery, EarlyView.This perspective highlights how knowledge‐guided artificial intelligence can address key challenges in manufacturing inverse design, including high‐dimensional search spaces, limited data, and process constraints. It focused on three complementary pillars—expert‐guided problem definition, physics‐informed machine learning, and large language model ...
Hugon Lee +3 more
wiley +1 more source
Cardiac disease diagnosis based on GAN in case of missing data.
PLoS ONEIn daily life, two common algorithms are used for collecting medical disease data: data integration of medical institutions and questionnaires. However, these statistical methods require collecting data from the entire research area, which consumes a ...
Xing Chen +8 more
doaj +1 more source
Advanced Intelligent Discovery, EarlyView.Sequential multicolor fluorescence imaging in dynamic microsystems is constrained by acquisition speed and excitation dose. This study introduces a real‐time framework to reconstruct spectrally separated channels from reduced cross‐channel acquisitions (frames containing mixed spectral contributions).
Juan J. Huaroto +3 more
wiley +1 more source
Ensembles of Generative Adversarial Networks
CoRR, 2016 accepted NIPS 2016 Workshop on Adversarial ...
Yaxing Wang +2 more
openaire +2 more sources
Cell Segmentation Beyond 2D—A Review of the State‐of‐the‐Art
Advanced Intelligent Discovery, EarlyView.Cell segmentation underpins many biological image analysis tasks, yet most deep learning methods remain limited to 2D despite the inherently 3D nature of cellular processes. This review surveys segmentation approaches beyond 2D, comparing 2.5D and fully 3D methods, analyzing 31 models and 32 volumetric datasets, and introducing a unified reference ...
Fabian Schmeisser +6 more
wiley +1 more source