By eliminating the need to alter the source images, this paper introduces a secure technique for coverless image steganography that strengthens defense against steganalysis attacks. Our method makes use of a hybrid Generative Adversarial Network (GAN...
Recent advancements in deep learning have led to significant improvements in pneumoconiosis diagnosis from chest X-rays (CXR). However, these models typically require large training datasets, which are challenging to collect due to the rarity of the ...
Biomedical physics & engineering express
Nov 27, 2025
Sparse-view low-dose computed tomography (LDCT) imaging poses difficulties in preserving image quality while reducing radiation exposure. Recent research has focused extensively on artificial intelligence (AI) to reduce artifacts in LDCT. This paper ...
Biomedical physics & engineering express
Nov 25, 2025
As physiological artifacts commonly overlap with EEG signals in both time and frequency domains, developing an effective end-to-end EEG artifact removal method is essential for a brain-computer interface (BCI) system. An end-to-end artifact removal m...
Virtual reality (VR) integrates technologies like computer graphics, artificial intelligence, and multi-sensor systems, creating transformative tools for designers and users. This study proposes a novel urban landscape design method using 3D laser sc...
Fault detection in high-speed train wheelset bearings is paramount for ensuring operational safety. However, the scarcity of fault samples limits the accuracy of traditional detection methods. To address this challenge, this paper proposes a supervis...
Traditional fish classification systems suffer from limited training data and imbalanced datasets, particularly for rare or morphologically complex species. This paper presents a novel Generative Adversarial Network architecture that integrates adapt...
In response to the limited detection accuracy of traditional orthogonal frequency division multiplexing systems in complex wireless channel environments, this study first uses conditional generative adversarial networks to construct a single input/ou...
PURPOSE: Manual segmentation of retinal blood vessels in fundus images has been widely used for detecting vascular occlusion, diabetic retinopathy, and other retinal conditions. However, existing automated methods face challenges in accurately segmen...
Journal of chemical information and modeling
Sep 22, 2025
In this work, we introduce auxiliary discriminator sequence generative adversarial networks (ADSeqGAN), a novel approach for molecular generation in small-sample data sets. Traditional generative models often struggle with limited training data, part...
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