Search Results - adversarial autoencoder networks

RETRACTION: DAE‐GAN: An Autoencoder Based Adversarial Network for Gaussian Denoising

“…RETRACTION: A. Samanta, A. Saha, S. C. Satapathy, H. Lin, “DAE‐GAN: An Autoencoder Based Adversarial Network for Gaussian Denoising,” Expert Systems (Early View): e12709, https://doi.org/10.1111/exsy.12709…”
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Adversarial Autoencoder Network for Hyperspectral Unmixing by Jin, Qiwen, Ma, Yong, Fan, Fan, Huang, Jun, Mei, Xiaoguang, Ma, Jiayi

“… Since the unmixing procedure can be explained as finding a set of low-dimensional representations that reconstruct the data with their corresponding bases, autoencoders (AEs…”
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Advancing Speech Enhancement with Generative Adversarial Network-Autoencoder: A Robust Adversarial Autoencoder Approach by Diwakar, Mandar, Gupta, Brijedra

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RETRACTED: DAE‐GAN: An autoencoder based adversarial network for Gaussian denoising by Samanta, Abhishek, Saha, Aheli, Satapathy, Suresh Chandra, Lin, Hong

“…), which has demonstrated considerably better results than the prior methods. There has been recent advancements in approaching the problem using generative adversarial networks (GAN…”
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Spatio‐Temporal Hourly and Daily Ozone Forecasting in China Using a Hybrid Machine Learning Model: Autoencoder and Generative Adversarial Networks by Cheng, Meiling, Fang, Fangxin, Navon, Ionel M., Zheng, Jie, Tang, Xiao, Zhu, Jiang, Pain, Christopher

“…‐scale numerical simulations. In this work, we introduce a hybrid model (VAE‐GAN) combining a generative adversarial network (GAN…”
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Perceptual Loss-Constrained Adversarial Autoencoder Networks for Hyperspectral Unmixing by Zhao, Min, Wang, Mou, Chen, Jie, Rahardja, Susanto

“… To cope with this issue, we propose a general perceptual loss-constrained adversarial autoencoder network for hyperspectral unmixing…”
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3D-Convolutional Neural Network with Generative Adversarial Network and Autoencoder for Robust Anomaly Detection in Video Surveillance by Shin, Wonsup, Bu, Seok-Jun, Cho, Sung-Bae

“… We propose a hybrid deep learning model composed of a video feature extractor trained by generative adversarial network with deficient anomaly data and an anomaly detector boosted by transferring the extractor…”
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Anomaly Detection With Memory-Augmented Adversarial Autoencoder Networks for Industry 5.0 by Zhang, Huan, Kumar, Neeraj, Wu, Sheng, Wu, Chunlei, Wang, Jian, Zhang, Peiying

“… In this paper, we propose Memory-augmented Adversarial Autoencoder with CNN-Transformer (CTMAANet), aiming to improve the quality and utilization of features, which is conducive to the innovation of detection technology under Industry…”
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A3N: Attention-based adversarial autoencoder network for detecting anomalies in video sequence by Aslam, Nazia, Rai, Prateek Kumar, Kolekar, Maheshkumar H.

“…This paper presents a novel attention-based adversarial autoencoder network (A3N) that consists of a two-stream decoder to detect abnormal events in video sequences…”
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AEGAN: Generating imperceptible face synthesis via autoencoder‐based generative adversarial network by Che, Aolin, Yang, Jing‐Hua, Guo, Cai, Dai, Hong‐Ning, Xie, Haoran, Li, Ping

“… Specifically, we design a generative adversarial network (GAN) framework with an autoencoder (AEGAN…”
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Anomalous node detection in attributed social networks using dual variational autoencoder with generative adversarial networks by Khan, Wasim, Abidin, Shafiqul, Arif, Mohammad, Ishrat, Mohammad, Haleem, Mohd, Shaikh, Anwar Ahamed, Farooqui, Nafees Akhtar, Faisal, Syed Mohd

“…Many types of real-world information systems, including social media and e-commerce platforms, can be modelled by means of attribute-rich, connected networks…”
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Generative Adversarial Autoencoder Network for Anti-Shadow Hyperspectral Unmixing by Sun, Bin, Su, Yuanchao, Sun, He, Bai, Jinying, Li, Pengfei, Liu, Feng, Liu, Dongsheng

“… In this letter, we employ a generative adversarial autoencoder (GAA) to develop a supervised unmixing method that can substantially reduce the impacts of shadow for unmixing…”
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Generative adversarial network constrained multiple loss autoencoder: A deep learning‐based individual atrophy detection for Alzheimer's disease and mild cognitive impairment by Shi, Rong, Sheng, Can, Jin, Shichen, Zhang, Qi, Zhang, Shuoyan, Zhang, Liang, Ding, Changchang, Wang, Luyao, Wang, Lei, Han, Ying, Jiang, Jiehui

“… Here, we proposed a framework called generative adversarial network constrained multiple loss autoencoder (GANCMLAE…”
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A Hybrid Deep Learning Model for E‐Commerce Recommendations: Sentiment Analysis With Autoencoders and Generative Adversarial Networks by Yarjanli, Mohammad, Mahdinasab, Neda

“…) unit, which is trained with a modified generative adversarial network (GAN). TLSTM leverages transductive learning to emphasize training samples that closely…”
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Integration of Adversarial Autoencoders With Residual Dense Convolutional Networks for Estimation of Non‐Gaussian Hydraulic Conductivities by Mo, Shaoxing, Zabaras, Nicholas, Shi, Xiaoqing, Wu, Jichun

“… In this study, we develop a convolutional adversarial autoencoder (CAAE) to parameterize non‐Gaussian conductivity fields with heterogeneous conductivity within each facies using a low…”
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AEGANAuth: Autoencoder GAN-Based Continuous Authentication With Conditional Variational Autoencoder Generative Adversarial Network by Li, Yantao, Ouyang, Caike, Huang, Hongyu

“… In this article, we present AEGANAuth, a lightweight and effective autoencoder GAN (AEGAN)-based continuous Authentication system for mobile devices using conditional variational autoencoder generative adversarial network (CVAEGAN…”
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Multi-Head Graph Attention Adversarial Autoencoder Network for Unsupervised Change Detection Using Heterogeneous Remote Sensing Images by Jia, Meng, Lou, Xiangyu, Zhao, Zhiqiang, Lu, Xiaofeng, Shi, Zhenghao

“… The MHGAN employs a bidirectional adversarial convolutional autoencoder network to reconstruct and perform style transformation of heterogeneous images…”
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Robust Sensor Fault Detection in Wireless Sensor Networks Using a Hybrid Conditional Generative Adversarial Networks and Convolutional Autoencoder by Khan, Rehan, Saeed, Umer, Koo, Insoo

“… As essential components of these systems, wireless sensor networks (WSNs) are installed in a wide range of diverse and often harsh environments…”
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Data augmentation for time series regression: Applying transformations, autoencoders and adversarial networks to electricity price forecasting by Demir, Sumeyra, Mincev, Krystof, Kok, Koen, Paterakis, Nikolaos G.

“… While existing time series augmentation methods have predominantly utilised feature space transformations to artificially expand training set sizes and boost prediction accuracies, we propose using autoencoders (AEs…”
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Reconstruction of incomplete surface electromyography based on an adversarial autoencoder network by Zou, Yongxiang, Cheng, Long, Han, Lijun

“… To address this issue, this paper proposes a novel adversarial autoencoder model, called the SGMD-AAE, which includes a self-mask generator and a multi-view discriminator…”
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