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Adversarial attack detection framework based on optimized weighted conditional stepwise adversarial network
Artificial Intelligence (AI)-based IDS systems are susceptible to adversarial attacks and face challenges such as complex evaluation methods,...
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Identity-Preserving Adversarial Training for Robust Network Embedding
Network embedding, as an approach to learning low-dimensional representations of nodes, has been proved extremely useful in many applications, e.g.,...
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Adversarial enhanced attributed network embedding
Attributed network embedding aims to extract latent features of complex networks from structural topology and node attributes. Existing embedding...
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Adversarial attack defense algorithm based on convolutional neural network
To improve the defense of CNN network traffic classifiers against adversarial sample attacks, the author proposes a batch adversarial training method...
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RSC-WSRGAN super-resolution reconstruction based on improved generative adversarial network
Traditional generative adversarial network models have made significant progress in generating high-quality images. However, there are still problems...
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RA-RevGAN: region-aware reversible adversarial example generation network for privacy-preserving applications
The rise of online sharing platforms has provided people with diverse and convenient ways to share images. However, a substantial amount of sensitive...
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Cycle mapping with adversarial event classification network for fake news detection
In recent years, there is a increase in researchers’ interest on social evidence, particularly for fake news detection (FND). However, news posts on...
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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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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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TCGAN: Three-Channel Generate Adversarial Network
Recently Image-to-image translation has achieve much progress in the literature. However, in exist method, border distortion, color distortion and...
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MvHAAN: multi-view hierarchical attention adversarial network for person re-identification
Person re-identification (re-id) aims to recognize pedestrians across different camera views, which enjoys popularity in computer vision area...
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Image inpainting based on tensor ring decomposition with generative adversarial network
Image inpainting is a fundamental task in the field of computer vision. However, there are three major challenges associated with this technique: (1)...
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A hybrid adversarial training for deep learning model and denoising network resistant to adversarial examples
Deep neural networks (DNNs) are vulnerable to adversarial attacks that generate adversarial examples by adding small perturbations to the clean...
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Video anomaly detection using diverse motion-conditioned adversarial predictive network
Video anomaly detection is always formulated as frame prediction task which only learned on normal data and detects deviations as anomalies. However,...
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FP-Net: frequency-perception network with adversarial training for image manipulation localization
Mining the forged regions of digitally tampered images is one of the key research tasks for visual recognition. Although there are many algorithms...
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Adversarial imitation learning-based network for category-level 6D object pose estimation
Category-level 6D object pose estimation is a very fundamental and key research in computer vision. In order to get rid of the dependence on the...
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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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Generative Adversarial Network Models for Anomaly Detection in Software-Defined Networks
Software-defined Networking (SDN) is a modern network management paradigm that decouples the data and control planes. The centralized control plane...
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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....
