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Generative Datalog and Answer Set Programming – Extended Abstract
Generative Datalog is an extension of Datalog that incorporates constructs for referencing parameterized probability distributions. This augmentation...
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Multistate time series imputation using generative adversarial network with applications to traffic data
Time series missing data is a pervasive problem in many fields, especially in intelligent transportation system, which hinders the application of...
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Distance Based Image Classification: A solution to generative classification’s conundrum?
Most classifiers rely on discriminative boundaries that separate instances of each class from everything else. We argue that discriminative...
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TransMRSR: transformer-based self-distilled generative prior for brain MRI super-resolution
Magnetic resonance images (MRI) acquired with low through-plane resolution compromise time and cost. The poor resolution in one orientation is...
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Generative adversarial networks for handwriting image generation: a review
Handwriting synthesis, the task of automatically generating realistic images of handwritten text, has gained increasing attention in recent years,...
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Application of deep generative networks for SAR/ISAR: a review
Military, agricultural, and urban planning have all made extensive use of SAR/ISAR in the realm of remote sensing. SAR/ISAR images are more capable...
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Virtual sample generation method based on generative adversarial fuzzy neural network
Key performance indicators of complex industrial process such as production quality and pollutant emissions concentration are difficult to be...
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PandoraGAN: Generating Antiviral Peptides Using Generative Adversarial Network
The continuous increase in pathogenic viruses and the intensive laboratory research emphasizes the need for cost- and time-efficient drug...
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Improved Generative Adversarial Network Learning via Structural Pattern Classification
Generative adversarial networks (GANs), as a leading class of generative models, have shown remarkable capacity in producing photo-realistic images....
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The application of evolutionary computation in generative adversarial networks (GANs): a systematic literature survey
As a subfield of deep learning (DL), generative adversarial networks (GANs) have produced impressive generative results by applying deep generative...
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Contrast enhancement of underwater images using conditional generative adversarial network
The scattering effect of light and the presence of water organism deteriorates image quality captured in underwater environment. Researchers have...
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Retrieval Augmented Modeling
Till this point in our book, we have discussed the fundamental principles of information retrieval, exploring its key elements, and various...
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ITrans: generative image inpainting with transformers
Despite significant improvements, convolutional neural network (CNN) based methods are struggling with handling long-range global image dependencies...
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Hypergraph Modeling
Hypergraph modeling is the fundamental task in hypergraph computation, which targets on establishing a high-quality hypergraph structure to...
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A generalized novel image forgery detection method using generative adversarial network
GANs (Generative Adversarial Networks) are widely employed in many domains of science and technology. They have produced high-resolution,...
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Advancing Medical Imaging Through Generative Adversarial Networks: A Comprehensive Review and Future Prospects
In medical imaging, traditional methods have long been relied upon. However, the integration of Generative Adversarial Networks (GANs) has sparked a...
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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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Dynamic adaptive generative adversarial networks with multi-view temporal factorizations for hybrid recovery of missing traffic data
Making reliable recovery of missing traffic data facilitates diverse applications of data-driven intelligent transportation system. But faced with...
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Creating Ad Campaigns Using Generative AI
Search campaigns consist of ad groups. An ad group contains a related set of keywords and ads. During an online campaign, search advertisers...
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A coupled generative graph convolution network by capturing dynamic relationship of regional flow for traffic prediction
Traffic flow prediction plays a critical role in urban traffic management and planning. Accurate prediction of traffic flow can enhance traffic...
