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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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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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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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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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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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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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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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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...
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GANAD: A GAN-based method for network anomaly detection
Cyber-intrusion always leads to severe threats to the network, i,e., system paralysis, information leaky, and economic losses. To protect network...
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MSG-Voxel-GAN: multi-scale gradient voxel GAN for 3D object generation
The Generative Adversarial Network (GAN) has been the subject of significant attention since it was introduced. It has been widely used in the image...
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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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A Novel Small Samples Fault Diagnosis Method Based on the Self-attention Wasserstein Generative Adversarial Network
In the current industrial production process, fault data of rotating machinery are often difficult to obtain, and a small amount of fault data can...
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VALD-GAN: video anomaly detection using latent discriminator augmented GAN
The most crucial and difficult challenge for intelligent video surveillance is to identify anomalies in a video that comprises anomalous behavior or...
