Results 131 to 140 of about 221,929 (334)

Deep Convolutional Generative Adversarial Networks in Image-Based Android Malware Detection

Computers
The recent advancements in generative adversarial networks have showcased their remarkable ability to create images that are indistinguishable from real ones.
Francesco Mercaldo, Fabio Martinelli, Antonella Santone   +2 more
doaj   +1 more source

Data augmentation using conditional generative adversarial network (cGAN): Application for prediction of corrosion pit depth and testing using neural network

, 2022
Haile Woldesellasse, Solomon Tesfamariam
openalex   +1 more source

LRFID-Net: A Local-Region-Based Fake-Iris Detection Network for Fake Iris Images Synthesized by a Generative Adversarial Network [PDF]

, 2023
Jung Soo Kim, Young Won Lee, Jin Seong Hong, Seung Gu Kim, Ganbayar Batchuluun, Kang Ryoung Park   +5 more
openalex   +1 more source

Artificial Intelligence Revolution in Transcriptomics: From Single Cells to Spatial Atlases

Advanced Science, EarlyView.
Single‐cell RNA sequencing and spatial transcriptomics have unveiled cellular heterogeneity and tissue organization with unprecedented resolution. Artificial intelligence (AI) now plays a pivotal role in interpreting these complex data. This review systematically surveys AI applications across the entire analytic workflow and offers practical guidance ...
Shixin Li, Tianxiang Xiao, Yuanyuan Lan, Chengxiao Wu, Zhouying Li, Rong Liu, Qing Fang, Chao Zhang   +7 more
wiley   +1 more source

A Generative Adversarial Network Model for Disease Gene Prediction With RNA-seq Data [PDF]

, 2020
Xue Jiang, Jingjing Zhao, Wei Qian, Weichen Song, Guan Ning Lin   +4 more
openalex   +1 more source

Machine Learning for Accelerating Energy Materials Discovery: Bridging Quantum Accuracy with Computational Efficiency

Advanced Energy Materials, EarlyView.
This perspective highlights how machine learning accelerates sustainable energy materials discovery by integrating quantum‐accurate interatomic potentials with property prediction frameworks. The evolution from statistical methods to physics‐informed neural networks is examined, showcasing applications across batteries, catalysts, and photovoltaics ...
Kwang S. Kim
wiley   +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

Dilated Spatial Generative Adversarial Networks for Ergodic Image Generation

, 2018
Generative models have recently received renewed attention as a result of adversarial learning. Generative adversarial networks consist of samples generation model and a discrimination model able to distinguish between genuine and synthetic samples.
Gasso, Gilles, Hérault, Romain, Laloy, Eric, Ruffino, Cyprien   +3 more
core  

Specific Emitter Identification with Limited Labelled Signals Based on Variational Autoencoder Embedded in Information‐Maximising Generative Adversarial Network and Gradient Penalty [PDF]

, 2022
CunXiang Xie, Limin Zhang, Zhaogen Zhong
openalex   +1 more source

Probabilistic Modeling for Prediction Errors to Enhance Balancing Market Participation of Photovoltaic Systems: Error Threshold Estimation, Multisite Aggregation, and Overloading Effects

Advanced Energy and Sustainability Research, EarlyView.
This study proposes a method to increase the value of solar power in balancing markets by managing prediction errors. The approach models prediction uncertainties and quantifies reserve requirements based on a probabilistic model. This enables the more reliable participation of photovoltaic plants in balancing markets across multiple sites, especially ...
Jindan Cui, Xue Fang, Takashi Oozeki, Yuzuru Ueda   +3 more
wiley   +1 more source