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Information-Minimizing Generative Adversarial Network for Fair Generation and Classification
Studies show that machine learning models trained from biased data can discriminate against groups with certain sensitive attributes. This problem...
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Robust generative adversarial network
Generative Adversarial Networks (GANs) are one of the most popular and powerful models to learn the complex high dimensional distributions. However,...
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Generative adversarial network for newborn 3D skeleton part segmentation
Childbirth simulations have been studied in order to predict and prevent difficult delivery issues. The reconstruction of the maternal pelvic model,...
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GAN-STD: small target detection based on generative adversarial network
With the development of convolutional neural networks, significant breakthroughs have been made in deep learning-based target detection algorithms....
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MTUNet + + : explainable few-shot medical image classification with generative adversarial network
Medical imaging, a cornerstone of disease diagnosis and treatment planning, faces the hurdles of subjective interpretation and reliance on...
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Mutual learning generative adversarial network
It is the key to realize high fidelity image-to-image translation to realize the precise disentangling of single domain feature based on the...
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Smart GAN: a smart generative adversarial network for limited imbalanced dataset
Advancements in Machine Learning (ML) and Computer Vision have led to notable improvements in the detection of breast cancer. However, the accuracy...
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PMGAN: pretrained model-based generative adversarial network for text-to-image generation
Text-to-image generation is a challenging task. Although diffusion models can generate high-quality images of complex scenes, they sometimes suffer...
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Efficient Segmentation of Vessels and Disc Simultaneously Using Multi-channel Generative Adversarial Network
Two-dimensional pictorial representation of the rear part of human eye furnish diagnostic information about blood vessels, optic disc, and macula....
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FGPGAN: a finer-grained CNN pruning via generative adversarial network
Model pruning has gained increasing attention in the field of network model compression. Although current methods combine GANs with model pruning,...
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TEGAN: Transformer Embedded Generative Adversarial Network for Underwater Image Enhancement
Underwater robots are widely used in underwater missions. However, due to complex scenes, it is difficult to obtain high-quality underwater images,...
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Restoration of damaged artworks based on a generative adversarial network
Ancient and contemporary artworks represent culture, heritage, and history. The artworks act as a bridge between the past and future of humankind....
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DDM-CGAN: a modified conditional generative adversarial network for SAR target image generation
In recent years, Generative Adversarial Network (GAN) have shown great potential and achieved excellent performance on the task of generating optical...
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Siamese conditional generative adversarial network for multi-focus image fusion
Multi-focus image fusion (MFIF) combines information by utilizing various image sequences of the same scenes at different of focus depths. The...
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Unsupervised video-based action recognition using two-stream generative adversarial network
Video-based action recognition faces many challenges, such as complex and varied dynamic motion, spatio-temporal similar action factors, and manual...
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MSGAN: multi-stage generative adversarial network-based data recovery in cyber-attacks
In an industrial control system, a programmable logic controller (PLC) plays a vital role in maintaining the stable operation of the system....
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TVA-GAN: attention guided generative adversarial network for thermal to visible image transformations
In the recent improvement in deep learning approaches for realistic image generation and translation, Generative Adversarial Networks (GANs)...
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VAEWGAN-NCO in image deblurring framework using variational autoencoders and Wasserstein generative adversarial network
This article proposes a novel “Deep Salient Image Deblurring (DSID) Framework” for kernel-free image deblurring that combines saliency detection and...
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Multi-scale information fusion generative adversarial network for real-world noisy image denoising
Image denoising is crucial for enhancing image quality, improving visual effects, and boosting the accuracy of image analysis and recognition. Most...
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AMMGAN: adaptive multi-scale modulation generative adversarial network for few-shot image generation
Deep learning-based methods have recently advanced image generation by exploiting the valuable information within immense training data, but they...
