Review on autoencoder and its application

Review on autoencoder and its application

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As a typical deep unsupervised learning model, autoencoder can automatically learn effective abstract features from unlabeled samples.In recent years, autoencoder has been widely used in target recognition, intrusion detection, fault diagnosis and many other fields.Thus, the theoretical basis, impro...

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Xehetasun bibliografikoak
Egile Nagusiak:	Jie LAI, Xiaodan WANG, Qian XIANG, Yafei SONG, Wen QUAN
Formatua:	Artikulua
Hizkuntza:	zho
Argitaratua:	Editorial Department of Journal on Communications 2021-09-01
Saila:	Tongxin xuebao
Gaiak:	autoencoder deep learning unsupervised learning feature extraction regularization
Sarrera elektronikoa:	http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2021160/

Antzeko izenburuak

Review on autoencoder and its application
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Dynamic Depth Learning in Stacked AutoEncoders
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Deep Convolution Neural Network and Autoencoders-Based Unsupervised Feature Learning of EEG Signals
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Nonlinear Unmixing via Deep Autoencoder Networks for Generalized Bilinear Model
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Isolation Forests and Deep Autoencoders for Industrial Screw Tightening Anomaly Detection
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Investigating Beta-Variational Convolutional Autoencoders for the Unsupervised Classification of Chest Pneumonia
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Auto encoder-guided Feature Extraction for Pneumonia Identification from Chest X-ray Images
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Disentangling Generative Factors of Physical Fields Using Variational Autoencoders
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Semi-Supervised Adversarial Variational Autoencoder
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