Search Results - Denoising-Autoencoder

Blind Denoising Autoencoder by Majumdar, Angshul

“…The term "blind denoising" refers to the fact that the basis used for denoising is learned from the noisy sample itself during denoising. Dictionary learning-…”
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DEVDAN: Deep evolving denoising autoencoder by Ashfahani, Andri, Pratama, Mahardhika, Lughofer, Edwin, Ong, Yew-Soon

“…The Denoising Autoencoder (DAE) enhances the flexibility of data stream method in exploiting unlabeled samples…”
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Noise Learning-Based Denoising Autoencoder by Lee, Woong-Hee, Ozger, Mustafa, Challita, Ursula, Sung, Ki Won

“…This letter introduces a new denoiser that modifies the structure of denoising autoencoder (DAE…”
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uDAS: An Untied Denoising Autoencoder With Sparsity for Spectral Unmixing by Qu, Ying, Qi, Hairong

“…Linear spectral unmixing is the practice of decomposing the mixed pixel into a linear combination of the constituent endmembers and the estimated abundances…”
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Conditional Generative Denoising Autoencoder by Karatsiolis, Savvas, Schizas, Christos N.

“…We present a generative denoising autoencoder model that has an embedded data classifier in its architecture in order to take advantage of class-based discriminating features and produce better data samples…”
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An enhancement denoising autoencoder for rolling bearing fault diagnosis by Meng, Zong, Zhan, Xuyang, Li, Jing, Pan, Zuozhou

“… Denoising autoencoders can automatically learn in-depth features from complex data and extract concise expressions, which are used in fault diagnosis…”
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Fault diagnosis of rotary machinery components using a stacked denoising autoencoder-based health state identification by Lu, Chen, Wang, Zhen-Ya, Qin, Wei-Li, Ma, Jian

“… improvements, and economical efficiency. This paper investigates an effective and reliable deep learning method known as stacked denoising autoencoder (SDA…”
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Automatic Fabric Defect Detection with a Multi-Scale Convolutional Denoising Autoencoder Network Model by Mei, Shuang, Wang, Yudan, Wen, Guojun

“… This approach is used to reconstruct image patches with a convolutional denoising autoencoder network at multiple Gaussian pyramid levels and to synthesize detection results from the corresponding resolution channels…”
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Robust Monitoring and Fault Isolation of Nonlinear Industrial Processes Using Denoising Autoencoder and Elastic Net by Yu, Wanke, Zhao, Chunhui

“… In this brief, a novel method denoising autoencoder and elastic net (DAE-EN) is proposed to solve the aforementioned issues by effectively integrating DAE and EN…”
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Deep Architecture for High-Speed Railway Insulator Surface Defect Detection: Denoising Autoencoder With Multitask Learning by Kang, Gaoqiang, Gao, Shibin, Yu, Long, Zhang, Dongkai

“…The insulator is an important catenary component that maintains the insulation between the catenary and earth. Due to the long-term impact of railway vehicles…”
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Wind Turbine Fault Detection Using a Denoising Autoencoder With Temporal Information by Jiang, Guoqian, Xie, Ping, He, Haibo, Yan, Jun

“… To this end, this paper proposes a new fault detector based on a recently developed unsupervised learning method, denoising autoencoder (DAE…”
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Electricity theft detection based on stacked sparse denoising autoencoder by Huang, Yifan, Xu, Qifeng

“…Inspired by the powerful feature extraction and the data reconstruction ability of autoencoder, a stacked sparse denoising autoencoder is developed for electricity theft detection in this paper…”
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Denoising Autoencoder Self-Organizing Map (DASOM) by Ferles, Christos, Papanikolaou, Yannis, Naidoo, Kevin J.

“… A fundamental approach is the use of higher-level representations devised by restricted Boltzmann machines and (denoising) autoencoders…”
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Feature learning from incomplete EEG with denoising autoencoder by Li, Junhua, Struzik, Zbigniew, Zhang, Liqing, Cichocki, Andrzej

“…An alternative pathway for the human brain to communicate with the outside world is by means of a brain computer interface (BCI). A BCI can decode…”
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State of charge estimation of lithium-ion battery using denoising autoencoder and gated recurrent unit recurrent neural network by Chen, Junxiong, Feng, Xiong, Jiang, Lin, Zhu, Qiao

“… processing method with the conventional gated recurrent unit recurrent neural network (GRU-RNN) method. First, a denoising autoencoder neural network…”
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Automated feature learning for nonlinear process monitoring – An approach using stacked denoising autoencoder and k-nearest neighbor rule by Zhang, Zehan, Jiang, Teng, Li, Shuanghong, Yang, Yupu

“…•Automated feature learning based on stacked denoising autoencoder (SDAE) and k-nearest neighbor rule (kNN…”
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Target Detection With Unconstrained Linear Mixture Model and Hierarchical Denoising Autoencoder in Hyperspectral Imagery by Li, Yunsong, Shi, Yanzi, Wang, Keyan, Xi, Bobo, Li, Jiaojiao, Gamba, Paolo

“… mixture model and deep learning. Our proposed detector firstly reduces interference via a specifically designed deep-learning-based hierarchical denoising autoencoder, and then carries out accurate detection with a two-step subspace…”
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Adaptive denoising autoencoder for robust fault detection by Li, Zixuan, Zhao, Haitao

“… Although denoising autoencoder can realize robust fault detection to a certain extent, its performance is limited by the addition of artificial noise, which refers to Gaussian noise or the dropout noise…”
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Stacked pruning sparse denoising autoencoder based intelligent fault diagnosis of rolling bearings by Zhu, Haiping, Cheng, Jiaxin, Zhang, Cong, Wu, Jun, Shao, Xinyu

“…This paper proposes a new stacked pruning sparse denoising autoencoder (sPSDAE) model for intelligent fault diagnosis of rolling bearings…”
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A correlative denoising autoencoder to model social influence for top- N recommender system by PAN, Yiteng, HE, Fazhi, YU, Haiping

“… Towards this problem, we propose a novel correlative denoising autoencoder (CoDAE) method by taking correlations between users with multiple roles into account…”
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