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Wasserstein GAN-based architecture to generate collaborative filtering synthetic datasets
Currently, generative applications are resha** different fields, such as art, computer vision, speech processing, and natural language. The...
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A Wasserstein GAN for Joint Learning of Inpainting and Spatial Optimisation
Image inpainting is a restoration method that reconstructs missing image parts. However, a carefully selected mask of known pixels that yield a high...
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Shared wasserstein adversarial domain adaption
In numerous real-world applications, obtaining labeled data for a specific deep learning task can be prohibitively expensive. We present an...
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An Innovative Approach for Long ECG Synthesis with Wasserstein GAN Model
Deep neural networks (DNNs) have set new standards in identifying and classifying irregular patterns in ECG (electrocardiogram) signals, surpassing...
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An Embedding Carrier-Free Steganography Method Based on Wasserstein GAN
Image has been widely studied as an effective carrier of information steganography, however, low steganographic capacity is a technical problem that...
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Wasserstein Adversarial Variational Autoencoder for Sequential Recommendation
Variational autoencoders (VAEs) have shown unique advantages as a generative model for sequence recommendation. The core of VAEs is the...
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DerainGAN: Single image deraining using wasserstein GAN
Rainy weather greatly affects the visibility of salient objects and scenes in the captured images and videos. The object/scene visibility varies with...
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Spatial and channel attention-based conditional Wasserstein GAN for direct and rapid image reconstruction in ultrasound computed tomography
Ultrasound computed tomography (USCT) is an emerging technology that offers a noninvasive and radiation-free imaging approach with high sensitivity,...
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A Self-Attention Based Wasserstein Generative Adversarial Networks for Single Image Inpainting
AbstractWith the popularization of portable devices such as mobile phones and cameras, digital images have been widely disseminated in human life....
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Algorithm for Generating Tire Defect Images Based on RS-GAN
Aiming at the problems of poor image quality, unstable training process and slow convergence speed in the data expansion method for generating...
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Wasserstein generative adversarial networks for modeling marked events
Marked temporal events are ubiquitous in several areas, where the events’ times and marks (types) are usually interrelated. Point processes and their...
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Geological model automatic reconstruction based on conditioning Wasserstein generative adversarial network with gradient penalty
Due to the structure complexity and heterogeneity of the geological models, it is difficult for traditional methods to characterize the corresponding...
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An efficient GAN-based predictive framework for multivariate time series anomaly prediction in cloud data centers
Recently, a growing amount of time series data has been collected in cloud data centers, making anomaly detection for multivariate time series...
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Video captioning using transformer-based GAN
Video captioning is the process of automatically generating natural language descriptions of video content. Historically, most video captioning...
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Wasserstein GANs-Enabled Spectral Normalization on Credit Card Fraud Detection
Credit card fraud detection has become quite a crucial task to increase reliability of online financial transactions. The generative models have been...
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ICWGAN-GP: an image fusion method based on infrared compensator and wasserstein generative adversarial network with gradient penalty
The existing Generative adversarial network (GAN)-based infrared (IR) and visible (VIS) image fusion methods mainly used multiple discriminators to...
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Hybrid tri-memristor hyperchaotic map and application in Wasserstein Generative Adversarial Nets
Inspired by basic circuit connection methods, memristors can also be utilized in the construction of complex discrete chaotic systems. To investigate...
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Multi-residual unit fusion and Wasserstein distance-based deep transfer learning for mill load recognition
This paper proposes the ball mill load recognition algorithm (MRUF-WD) based on multi-residual unit fusion (MRUF) and Wasserstein distance transfer...
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Sliced Wasserstein Distance-Guided Three-Dimensional Porous Media Reconstruction Based on Cycle-Consistent Adversarial Network and Few-Shot Learning
Numerical simulation studies of water–rock interaction mechanisms and pore-scale multiphase flow properties often require high computational...
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On the Effect of Loss Function in GAN Based Data Augmentation for Fault Diagnosis of an Industrial Robot
Intelligent fault diagnosis often requires a balanced dataset which is hard to be obtained in industrial equipments, often resulting in an imbalance...