Search Results - "convolutional autoencoder network"

An unsupervised feature learning based health indicator construction method for performance assessment of machines by Guo, Liang, Yu, Yaoxiang, Duan, Andongzhe, Gao, Hongli, Zhang, Jiangquan

“…•A multi-scale CAE network is used to extract features from three scale levels.•Only the data collected under health conditions are used for network…”
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Broadband Communication Signal Detection Using Deep Convolutional Autoencoder and Spectrum Center Network by Wei, Bin

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Automatic classification with an autoencoder of seismic signals on a distributed acoustic sensing cable by Chien, Chih-Chieh, Jenkins, William F., Gerstoft, Peter, Zumberge, Mark, Mellors, Robert

“…This study probes the association between fluid injection in enhanced geothermal systems and certain kinds of seismicity that may result from hydraulic…”
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Fault state identification of rolling bearings based on deep transfer convolutional autoencoder and a new health indicator by Xiao, Jiafeng, Dong, Shaojiang

“…•A new health indicator (HI) using the maximum feature eigenenergy ratio of the envelope spectrum weighted by the standard deviation is proposed for monitoring…”
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Looseness Identification of Track Fasteners Based on Ultra-Weak FBG Sensing Technology and Convolutional Autoencoder Network by Li, Sheng, Jin, Liang, Jiang, Jinpeng, Wang, Honghai, Nan, Qiuming, Sun, Lizhi

“…Changes in the geological environment and track wear, and deterioration of train bogies may lead to the looseness of subway fasteners. Identifying loose…”
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A New SCAE-MT Classification Model for Hyperspectral Remote Sensing Images by Chen, Huayue, Chen, Ye, Wang, Qiuyue, Chen, Tao, Zhao, Huimin

“…Hyperspectral remote sensing images (HRSI) have the characteristics of foreign objects with the same spectrum. As it is difficult to label samples manually,…”
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Mineral Prospectivity Prediction by Integration of Convolutional Autoencoder Network and Random Forest by Yang, Na, Zhang, Zhenkai, Yang, Jianhua, Hong, Zenglin

“…The convolutional neural networks used widely in mineral prospectivity prediction usually perform mixed feature extraction for multichannel inputs. This…”
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Speaker Clustering by Co-Optimizing Deep Representation Learning and Cluster Estimation by Li, Yanxiong, Wang, Wucheng, Liu, Mingle, Jiang, Zhongjie, He, Qianhua

“…Speaker clustering is a task to merge speech segments uttered by the same speaker into a single cluster, which is an effective tool for alleviating the…”
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Unsupervised feature extraction with convolutional autoencoder with application to daily stock market prediction by Xie, Li, Yu, Sheng

“…Due to the volatility and noise of the stock market, accurately obtaining the trend of the stock market is a challenging problem, and gets the attention of…”
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Attention mechanism-based deep denoiser for desert seismic random noise suppression by Lin, Hongbo, Liu, Chang, Wang, Shigang, Ye, Wenhai

“…Seismic data collected from desert areas contain a large amount of low-frequency random noise with similar waveforms to the effective signals. The complex…”
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Segmentation of digital rock images using deep convolutional autoencoder networks by Karimpouli, Sadegh, Tahmasebi, Pejman

“…Segmentation is a critical step in Digital Rock Physics (DRP) as the original images are available in a gray-scale format. Conventional methods often use…”
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End-to-End Underwater Acoustic Communication Based on Autoencoder with Dense Convolution by Xie, Fangtong, Zhu, Yunan, Wang, Biao, Wang, Wu, Jin, Pian

“…To address the problems of the high complexity and poor bit error rate (BER) performance of traditional communication systems in underwater acoustic…”
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