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Conditional Wasserstein Generative Adversarial Network With W-Net and Wasserstein-L1-SSIM Loss Function for Single Image Dehazing

IEEE Access
Generative Adversarial Networks (GANs) have been widely used to solve different image translation problems. This article proposes an exploration of the Conditional Wasserstein Generative Adversarial Network (cWGAN) building blocks to improve its ...
Bijaylaxmi Das +3 more
doaj +1 more source

Generative Adversarial Network-based Parameter Optimization (GAN-PO)

<p>Code and datasets for the article: "Learning Distributed Parameters of Land Surface Hydrologic Models Using a Generative Adversarial Network "</p ...
Pan, Baoxiang, Sun, Ruochen, Duan, Qingyun +2 more
core +1 more source

Predicting Performance of Hall Effect Ion Source Using Machine Learning

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
This study introduces HallNN, a machine learning tool for predicting Hall effect ion source performance using a neural network ensemble trained on data generated from numerical simulations. HallNN provides faster and more accurate predictions than numerical methods and traditional scaling laws, making it valuable for designing and optimizing Hall ...
Jaehong Park +8 more
wiley +1 more source

Conditional noise generative adversarial networks with Siamese neural network for longer time series forecasting

Scientific Reports
Generative adversarial networks have achieved strong results in computer vision, but their use in time series forecasting remains limited. This paper proposes a conditional noise generative adversarial network with a Siamese neural network as ...
Haotian Mao, Xiao Feng
doaj +1 more source

Extended Semi-Supervised Learning Generative Adversarial Network

An extended semi-supervised learning (ESSL) generative adversarial network (GAN) including metrics for evaluating training performance and a method for generating an estimated label vector y by the extended semi-supervised learning (ESSL) generative ...
Scrofani, James, Tummala, Murali, Hahn, Andrew W. +2 more
core

BMPCQA: Bioinspired Metaverse Point Cloud Quality Assessment Based on Large Multimodal Models

Advanced Intelligent Systems, EarlyView.
This study presents a bioinspired metaverse point cloud quality assessment metric, which simulates the human visual evaluation process to perform the point cloud quality assessment task. It first extracts rendering projection video features, normal image features, and point cloud patch features, which are then fed into a large multimodal model to ...
Huiyu Duan +7 more
wiley +1 more source

Calibration‐Free Electromyography Motor Intent Decoding Using Large‐Scale Supervised Pretraining

Advanced Intelligent Systems, EarlyView.
Calibration‐free electromyography motor intent decoding is enabled through large‐scale supervised pretraining across heterogeneous datasets. A Spatially Aware Feature‐learning Transformer processes variable channel counts and electrode geometries, allowing transfer across users and recording setups. On a held‐out benchmark, fine‐tuned cross‐user models
Alexander E. Olsson +3 more
wiley +1 more source

CWGAN-GP with residual network model for lithium-ion battery thermal image data expansion with quantitative metrics

Energy and AI
Lithium batteries find extensive applications in energy storage. Temperature is a crucial indicator for assessing the state of lithium-ion batteries, and numerous experiments require thermal images of lithium-ion batteries for research purposes. However,
Fengshuo Hu +5 more
doaj +1 more source

Semi-supervised generative adversarial networks for improved colorectal polyp classification using histopathological images

Early and accurate detection of dysplasia in colorectal polyps can improve prognosis and increase survival chances. Recently, automated learning-based approaches using histopathological images have been adopted for improved classification of polyps.
Sharma, Vanshali +10 more
core +1 more source

Zero Watermarking Using Convolutional Additive Self‐Attention Vision Transformer and Discrete Wavelet Transform‐Variance‐Based Feature Descriptor for Medical Image Security in Mobile Healthcare Services

Advanced Intelligent Systems, EarlyView.
A zero‐watermarking algorithm that combines a refined convolutional additive self‐attention vision transformer (CAS‐ViT) with a discrete wavelet transform variance‐based feature descriptor (DVFD) is proposed for protecting the privacy of medical images in mobile healthcare services.
Pei Liu +6 more
wiley +1 more source

generative adversarial networks
deep learning
attention mechanism