Results 131 to 140 of about 3,042,897 (294)

Federated Learning for COVID-19 Detection With Generative Adversarial Networks in Edge Cloud Computing

, 2022
Federated Learning for COVID-19 Detection With Generative Adversarial Networks in Edge Cloud ...
A Seneviratne (13395066), M Ding (10262309), DC Nguyen (14286476), Pubudu Pathirana (13089972), AY Zomaya (9888527)   +4 more
core  

Accelerating Discovery of Organic Molecular Crystals via Materials Informatics and Autonomous Experiments

Advanced Intelligent Discovery, EarlyView.
Materials informatics and autonomous experimentation are transforming the discovery of organic molecular crystals. This review presents an integrated molecule–crystal–function–optimization workflow combining machine learning, crystal structure prediction, and Bayesian optimization with robotic platforms.
Takuya Taniguchi, Kazuki Ishizaki, Ryo Fukasawa   +2 more
wiley   +1 more source

Cardiac disease diagnosis based on GAN in case of missing data.

PLoS ONE
In 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, Na Zhang, Xiaohui Yang, Chunyan Wang, Qi Na, Tianyun Luan, Wendi Zhu, Chenjie Zhang, Chao Yang   +8 more
doaj   +1 more source

Probabilistic Generative Adversarial Networks

CoRR, 2017
We introduce the Probabilistic Generative Adversarial Network (PGAN), a new GAN variant based on a new kind of objective function. The central idea is to integrate a probabilistic model (a Gaussian Mixture Model, in our case) into the GAN framework which supports a new kind of loss function (based on likelihood rather than classification loss), and at ...
Hamid Eghbal-zadeh, Gerhard Widmer
openaire   +3 more sources

From Data to Discovery: Machine Learning–Enabled Intelligent Characterization of Two‐Dimensional Materials

Advanced Intelligent Discovery, EarlyView.
Machine learning serves as a central engine for the intelligent characterization of two‐dimensional materials by integrating multimodal techniques, including optical microscopy, spectroscopy, electron microscopy, and scanning probe microscopy (SPM). This unified framework enables automated, high‐throughput, and quantitative extraction of structural ...
Zhi‐Long Cao, Jia‐Xu Yan
wiley   +1 more source

Generative Adversarial Networks for Music Generation [PDF]

In this paper, we aim to harness a machine learning model called Genera- tive Adversarial Networks (GAN) in order to produce AI generated musical strands.
Berman, Harry
core   +1 more source

Optimizing Generative Adversarial Networks for Low Resolution Image Enhancement

, 2020
Our research focuses on optimizing the performance of Generative Adversarial Networks to increase image resolution through various methods and approaches.
Gonzalez, Maria, Hall, Justin
core  

Generative Adversarial Networks and Applications in Bioinformatics

, 2021
Generative Adversarial Networks (GAN) are currently considered a state-of-the-art method for image generation. Recently, Deep Convolutional Generative Adversarial Networks (DCGAN) yielded promising results in protein contact maps generation.
KOLESNICHENKO, Nikita
core  

A Generative AI Framework to Predict Cardiomyocyte Contraction Function From Single Static Images

Advanced Intelligent Discovery, EarlyView.
A single static hiPSC‐cardiomyocyte image is fed into a U‐Net‐GAN framework, which directly predicts a pixel‐resolved contraction heatmap without time‐lapse imaging. StyleGAN2‐generated synthetic cell–heatmap pairs augment training, improving prediction fidelity (SSIM = 0.84).
Andrew Kowalczewski, Chenyan Wang, Xinrui Wang, Huaxiao Yang, Zhao Qin, Zhen Ma   +5 more
wiley   +1 more source

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