Results 181 to 190 of about 4,829,196 (302)

Phase space sampling and operator confidence with generative adversarial networks

, 2017
We demonstrate that a generative adversarial network can be trained to produce Ising model configurations in distinct regions of phase space. In training a generative adversarial network, the discriminator neural network becomes very good a discerning ...
Mills, Kyle, Tamblyn, Isaac
core   +1 more source

Electrospun Porous Materials for the Next‐Generation Proton Exchange Membrane Fuel Cells: Progress, Challenges, and AI‐Optimized Perspectives

Carbon Energy, EarlyView.
Incorporating AI to optimize solution, process, and environment enables efficient prediction of structural properties and performance, allowing tailoring of GDL, CL, and PEM fabrication to guide PEMFC toward 9.0 kW L‒1 by 2040. ABSTRACT The performance and commercial viability of proton exchange membrane fuel cells (PEMFCs) are constrained by key ...
Shangfeng Jiang, Panfeng Wang, You Gong, Zeyu Sun, Huatan Chen, Geng Wang, Ting Tao, Chuang Zhai, Xi Wang, Ruixin Chen, Jiaxin Jiang, Bingrong Zhang   +11 more
wiley   +1 more source

Enzymatic Electrosynthesis for Sustainable CO2 Conversion: Advancing Circular Carbon Economy

Carbon Energy, EarlyView.
Enzymatic electrosynthesis (EES) offers molecular precision in synthesizing value‐added products from CO2. We highlight its distinct edge over alternative enzyme‐hybrid systems and analyze electron transfer pathways. Key strategies to overcome electron transfer bottlenecks and expand product diversity are addressed, and also data‐driven approaches for ...
Yan Xie, Jia Ouyang, Manu Suvarna, Xiangzhou Yuan, Matthew R. Hill, Uwe Bornscheuer, Huiyan Zhang, Yong Sik Ok   +7 more
wiley   +1 more source

GAN-MD: A myocarditis detection using multi-channel convolutional neural networks and generative adversarial network-based data augmentation

GAN-MD: A myocarditis detection using multi-channel convolutional neural networks and generative adversarial network-based data ...
Roohallah Alizadehsani (13057710), A Azadbar (18399516), JM Gorriz (7788572), H Ahmadi Golilarz (18399513)   +3 more
core   +1 more source

DHAFGan: A dense hybrid attention fusion generative adversarial network for infrared and visible image fusion. [PDF]

PLoS One
Hong Q, Xu Z, Qin D, Zheng Y, Zhang H.
europepmc   +1 more source

Beyond the Human Negotiator: Generative AI and the Threshold of Autonomous Decision‐Making

Conflict Resolution Quarterly, EarlyView.
ABSTRACT This article provides a comprehensive framework for understanding the role of artificial intelligence (AI) in negotiation, evaluating contemporary systems through the specific case study of Large Language Models (LLMs). To address the lack of established terminology, it first proposes a new typology distinguishing Negotiation Supported by AI ...
Martin Svatos
wiley   +1 more source

Application of Hyperspectral Imaging and Generative Adversarial Network for Powdery Mildew Severity Detection on Melon Leaves. [PDF]

Plants (Basel)
Hong Z, Zhang C, Fang L, Ye H, Fang H, He Y.   +5 more
europepmc   +1 more source

Research progress and current status of dynamic wave propagation characteristics in rock mass: A review

Deep Underground Science and Engineering, EarlyView.
This review elucidates the velocity–dispersion–attenuation coupling mechanisms of wave propagation in rock masses, compares six representative models, and reveals how pressure, temperature, mineral composition, and anisotropy jointly control dynamic responses in complex geological media.
Jiajun Shu, Tao Li, Ruiqi Yuan, Yue Li, Bingni Wu, Bo Liu, Zhengding Deng, Galindo Rubén, Fausto Molina‐Gómez   +8 more
wiley   +1 more source

Multi-modality brain tumor segmentation using dual-attention generative adversarial network. [PDF]

Rep Pract Oncol Radiother
Kawahara D, Nishimura T, Tsuneda M, Okamoto H, Nakamura M, Nishio T, Murakami Y.   +6 more
europepmc   +1 more source

Advances in vital‐sign prediction and early‐warning models for underground coal mine workers integrating environmental factors

Deep Underground Science and Engineering, EarlyView.
This review synthesizes advances in predicting miners' vital signs by integrating environmental monitoring (dust, temperature, and gas) with physiological data. It highlights multi‐source data fusion techniques and early‐warning models for enhanced occupational safety in underground coal mines.
Junji Zhu, Dawei Cui, Yingjie Liu, Yuntao Liang, Yue Zhang   +4 more
wiley   +1 more source