Search Results - "convolutional autoencoder network"

Multi-stage convolutional autoencoder network for hyperspectral unmixing by Yu, Yang, Ma, Yong, Mei, Xiaoguang, Fan, Fan, Huang, Jun, Li, Hao

“…Hyperspectral unmixing (HU) is a fundamental and critical task in various hyperspectral image (HSI) applications. Over the past few years, the linear mixing…”
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Convolutional autoencoder network lithology recognition based on scratch tests by Wang, Suling, Ren, Zhihui, Dong, Kangxing, Li, Yanchun, Li, Jinbo, Wen, Pengyun, Qu, Ruyi, Li, Tingting, Wen, Zhennan

“…To address the characteristic of frequent lithological alternations in the continental shale of the Songliao Basin in China and meet the refined requirements…”
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Single-pixel imaging with untrained convolutional autoencoder network by Li, Zhicai, Huang, Jian, Shi, Dongfeng, Chen, Yafeng, Yuan, Kee, Hu, Shunxing, Wang, Yingjian

“…•We propose a physical model-driven untrained deep convolutional autoencoder network for SPI and validate its performance from simulations and experiments…”
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Bayesian optimization and channel-fusion-based convolutional autoencoder network for fault diagnosis of rotating machinery by Zou, L., Zhuang, K.J., Zhou, A., Hu, J.

“…•A novel convolutional network based on Bayesian optimization and channel fusion mechanism is developed.•The proposed method is applied to extract the…”
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Segmentation of backscattered electron images of geopolymers using convolutional autoencoder network by Sheiati, Shohreh, Behboodi, Sanaz, Ranjbar, Navid

“…•An automatic CNN-based model is presented for multi-phase segmentation of BSE images.•The proposed model compares with conventional segmentation…”
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A targeted one dimensional fully convolutional autoencoder network for intelligent compression of magnetic flux leakage data by Xuan, Wenbo, Chen, Pengchao, Li, Rui, Wang, Fuxiang, Fu, Kuan, Wen, Zhitao

“…) non-destructive testing in oil and gas pipelines, an intelligent data compression method based on a targeted one-dimensional fully convolutional autoencoder network is proposed…”
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A Novel Spatiotemporal Enhanced Convolutional Autoencoder Network for Unsupervised Health Indicator Construction by Li, Shuaiyong, Zhang, Chao, Zhang, Xuyuntao

“…The health indicator (HI) of rotating machinery affects the reliability and accuracy of its remaining useful life (RUL) prediction. Convolutional autoencoder…”
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Cascaded hybrid convolutional autoencoder network for spectral-spatial nonlinear hyperspectral unmixing by Wu, Jinbin, Zhao, Jiankang, Long, Haihui

“…Due to the complex interaction of photons between materials, linear hyperspectral unmixing (HU) is limited in real scenarios, making nonlinear unmixing a…”
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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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Local phase-constrained convolutional autoencoder network for identifying multivariate geochemical anomalies by Liu, Qiliang, Wu, Gusheng, Liu, Zhankun, Mao, Xiancheng, Yang, Jie, Deng, Min

“… This study proposed a local Phase-Constrained Convolutional AutoEncoder network (PC-CAE) for the identification of multivariate geochemical anomalies…”
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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

“… To solve this limitation, this paper utilized convolutional autoencoder networks to mine latent high-level features for each predictor variable in parallel to prevent the mixing of features…”
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Inpainting non-anatomical objects in brain imaging using enhanced deep convolutional autoencoder network by Kumar, Puranam Revanth, Shilpa, B, Jha, Rajesh Kumar, Raju, B Deevena, Mohammed, Thayyaba Khatoon

“… In this paper, we proposed a deep convolutional autoencoder network with improved parameters as a robust method for inpainting non-anatomical objects in MRI and CT images…”
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CAEM-GBDT: a cancer subtype identifying method using multi-omics data and convolutional autoencoder network by Shen, Jiquan, Guo, Xuanhui, Bai, Hanwen, Luo, Junwei

“… autoencoder network to identify cancer subtypes…”
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Vector Quantized Convolutional Autoencoder Network for LDCT Image Reconstruction with Hybrid Loss by Ramanathan, Shalini, Ramasundaram, Mohan

“…Medical image reconstruction is the process of creating high-quality and accurate images. During acquisition, these devices capture raw measurements or signals…”
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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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Speech Enhancement using Convolutional Autoencoder Network by Sengupta, Subhadeep, Rihal, Pranav, D’Souza, Allwin

“…Abstract—We present an end-to-end deep learning approach to denoising speech signals by processing the raw waveform directly. Given input audio containing…”
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Multi-classification recognition method of arc fault based on convolutional autoencoder network by Li, Kui, Zhang, Dan, Wang, Yao

“… The arc fault protection device is prone to malfunction. A multi-class recognition method of arc fault based on convolutional autoencoder network was proposed…”
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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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Broadband Communication Signal Detection Using Deep Convolutional Autoencoder and Spectrum Center Network by Wei, Bin

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