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N-GAN: a novel anomaly-based network intrusion detection with generative adversarial networks
Network intrusion detection is one of the popular cyber defense mechanisms, which entails detection of cyber threat at network layer level....
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Alzheimer’s disease classification using 3D conditional progressive GAN- and LDA-based data selection
Alzheimer’s disease is a kind of neurological disorder that directly impacts the memory of a patient. Structural magnetic resonance imaging (sMRI) is...
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TenGAN: adversarially generating multiplex tensor graphs
In this work, we explore multiplex graph (networks with different types of edges) generation with deep generative models. We discuss some of the...
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An Asymmetric Two-Sided Penalty Term for CT-GAN
Generative Adversarial Networks (GAN) is undoubtedly one of the most outstanding deep generation models in the tasks such as image-to-image...
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AU-GAN: Attention U-Net Based on a Built-In Attention for Multi-domain Image-to-Image Translation
Multi-domain image-to-image translation refers to map** images from a source domain to multiple target domains. The state-of-the-art deep learning...
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GAN Attacks and Counterattacks in Federated Learning
In this chapter, we will present the related content of generative adversarial networks (GANs) and their applications in the federated learning...
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Low-light image enhancement based on GAN with attention mechanism and color Constancy
Images captured in low-light often suffer from severe quality degraded problems, such as low contrast and color distortion, which make it intractable...
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ISP-GAN: inception sub-pixel deconvolution-based lightweight GANs for colorization
Though there are many encouraging reports, existing image colorization algorithms are still prone to unnatural visual distortions. We observe that...
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Wasserstein Generative Adversarial Networks for Realistic Traffic Sign Image Generation
Recently, Convolutional neural networks (CNN) with properly annotated training data and results will obtain the best traffic sign detection (TSD) and...
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Improved Transformer-Based Implicit Latent GAN with Multi-headed Self-attention for Unconditional Text Generation
Generative Adversarial Network (GAN) is widely used in computer vision, such as image generation and other tasks. In recent years, GAN has also been...
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An Effective WGAN-Based Anomaly Detection Model for IoT Multivariate Time Series
This paper studies an effective unsupervised deep learning model for multivariate time series anomaly detection. Since multivariate time series...
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Federated Learning with GAN-Based Data Synthesis for Non-IID Clients
Federated learning (FL) has recently emerged as a popular privacy-preserving collaborative learning paradigm. However, it suffers from the...
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Adversarial training with Wasserstein distance for learning cross-lingual word embeddings
Recent studies have managed to learn cross-lingual word embeddings in a completely unsupervised manner through generative adversarial networks...
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A WGAN-Based Generative Strategy in Evolutionary Multitasking for Multi-objective Optimization
Multitasking for multi-objective optimization (MTMO) is one of the most important issues in evolutionary computation. The information exchange...
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Wasserstein Distance-Based Auto-Encoder Tracking
Most of the existing visual object trackers are based on deep convolutional feature maps, but there have fewer works about finding new features for...
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Fast Unsupervised Residual Attention GAN for COVID-19 Detection
Recently, deep unsupervised learning methods based on Generative Adversarial Networks (GANs) have shown great potential for detecting anomalies....
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Brain MRI to PET Synthesis and Amyloid Estimation in Alzheimer’s Disease via 3D Multimodal Contrastive GAN
Positron emission tomography (PET) can detect brain amyloid-β (Aβ) deposits, a diagnostic hallmark of Alzheimer’s disease and a target for disease...
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Misalignment Insensitive Perceptual Metric for Full Reference Image Quality Assessment
Full-reference (FR) image quality assessment (IQA) is crucial in the evaluation of restored images by comparing them with pristine-quality reference...
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Synthetic Network Traffic Data Generation and Classification of Advanced Persistent Threat Samples: A Case Study with GANs and XGBoost
The need to develop more efficient network traffic data generation techniques that can reproduce the intricate features of traffic flows forms a...
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DuelGAN: A Duel Between Two Discriminators Stabilizes the GAN Training
In this paper, we introduce DuelGAN, a generative adversarial network (GAN) solution to improve the stability of the generated samples and to...