Search Results - "convolutional autoencoder(cae)"

CNN and Convolutional Autoencoder (CAE) based real-time sensor fault detection, localization, and correction by Jana, Debasish, Patil, Jayant, Herkal, Sudheendra, Nagarajaiah, Satish, Duenas-Osorio, Leonardo

“…Increasing advances in sensing technologies and analytics have led to the proliferation of sensors to monitor structural and infrastructural systems. Accurate…”
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Motor Fault Diagnosis and Detection with Convolutional Autoencoder (CAE) Based on Analysis of Electrical Energy Data by Choi, YuRim, Joe, Inwhee

“…This study develops a Convolutional Autoencoder (CAE) and deep neural network (DNN)-based model optimized for real-time signal processing and high accuracy in motor fault diagnosis…”
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Commonality Autoencoder: Learning Common Features for Change Detection From Heterogeneous Images by Wu, Yue, Li, Jiaheng, Yuan, Yongzhe, Qin, A. K., Miao, Qi-Guang, Gong, Mao-Guo

“… To combat this problem, we propose an unsupervised change detection method that contains only a convolutional autoencoder (CAE…”
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Deep convolutional autoencoder for radar-based classification of similar aided and unaided human activities by Seyfioglu, Mehmet Saygin, Ozbayoglu, Ahmet Murat, Gurbuz, Sevgi Zubeyde

“… Moreover, a three-layer, deep convolutional autoencoder (CAE) is proposed, which utilizes unsupervised pretraining to initialize the weights in the subsequent convolutional layers…”
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A Particle Swarm Optimization-Based Flexible Convolutional Autoencoder for Image Classification by Sun, Yanan, Xue, Bing, Zhang, Mengjie, Yen, Gary G.

“…Convolutional autoencoders (CAEs) have shown their remarkable performance in stacking to deep convolutional neural networks (CNNs…”
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One-Dimensional Residual Convolutional Autoencoder Based Feature Learning for Gearbox Fault Diagnosis by Yu, Jianbo, Zhou, Xingkang

“…Vibration signals are generally utilized for machinery fault diagnosis to perform timely maintenance and then reduce losses. Thus, the feature extraction on…”
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An anomaly detection method for gas turbines based on single-condition training with zero-fault sample by Yue, Yubin, Wang, Hongjun, Zhang, Peishuo, Gu, Fengshou

“…Enhancing anomaly detection performance is essential for effective gas turbine condition monitoring and health maintenance. However, in industrial…”
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FedRUL: A New Federated Learning Method for Edge-Cloud Collaboration Based Remaining Useful Life Prediction of Machines by Guo, Liang, Yu, Yaoxiang, Qian, Mengui, Zhang, Ruiqi, Gao, Hongli, Cheng, Zhe

“… Each client includes a convolutional autoencoder (CAE) comprised of an encoder and a decoder while the server…”
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Machine learning-based reduced-order reconstruction method for flow fields by Gao, Hu, Qian, Weixin, Dong, Jiankai, Liu, Jing

“…•Design of the ROR model framework based on partial differential operators.•Extraction of low-dimensional flow field features using an autoencoder.•Combination…”
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Intelligent framework for unsupervised damage detection in bridges using deep convolutional autoencoder with wavelet transmissibility pattern spectra by Li, Shuai, Cao, Yuxi, Gdoutos, Emmanuel E., Tao, Mei, Faisal Alkayem, Nizar, Avci, Onur, Cao, Maosen

“…Deep Learning has been increasingly utilized in structural damage detection. Existing relevant studies often highlight the benefits of supervised deep learning…”
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A Convolutional Autoencoder Method for Simultaneous Seismic Data Reconstruction and Denoising by Jiang, Jinsheng, Ren, Haoran, Zhang, Meng

“… As a consequence of the high efficiency and nonlinear fitting ability of deep learning models, we propose an improved convolutional autoencoder (CAE…”
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A convolutional autoencoder-based method for learning and ranking personal daylighting preference by Mah, Dongjun, Tzempelikos, Athanasios

“…: classifying daylighting preference and estimating ordinal ranking. This paper presents a two-stage training method for inferring the relative daylight preference from pairs of luminance maps using convolutional autoencoder (CAE…”
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Sky Image Prediction Model Based on Convolutional Auto-Encoder for Minutely Solar PV Power Forecasting by Fu, Yuwei, Chai, Hua, Zhen, Zhao, Wang, Fei, Xu, Xunjian, Li, Kangping, Shafie-Khah, Miadreza, Dehghanian, Payman, Catalao, Joao P. S.

“… To avoid these two deficiencies, convolutional autoencoder (CAE) based sky image prediction models are proposed…”
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Convolutional Autoencoder Model for Finger-Vein Verification by Hou, Borui, Yan, Ruqiang

“…This paper presents a novel deep learning-based method that integrates a Convolutional Auto-Encoder (CAE) with support vector machine (SVM) for finger-vein…”
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Unsupervised Change Detection Using Convolutional-Autoencoder Multiresolution Features by Bergamasco, Luca, Saha, Sudipan, Bovolo, Francesca, Bruzzone, Lorenzo

“… To overcome this limit, we propose an unsupervised CD method that exploits multiresolution deep feature maps derived by a convolutional autoencoder (CAE…”
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CAE-MAS: Convolutional Autoencoder Interference Cancellation for Multiperson Activity Sensing With FMCW Microwave Radar by Raeis, Hossein, Kazemi, Mohammad, Shirmohammadi, Shervin

“…Human activity sensing is a crucial component of health monitoring and smart environment applications. Frequency-modulated continuous-wave (FMCW) radars can be…”
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Unsupervised Hyperspectral Image Band Selection Based on Deep Subspace Clustering by Zeng, Meng, Cai, Yaoming, Cai, Zhihua, Liu, Xiaobo, Hu, Peng, Ku, Junhua

“…Hyperspectral image (HSI) consists of hundreds of continuous narrow bands with high redundancy, resulting in the curse of dimensionality and an increased…”
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Nonlinear reduced-order modeling for three-dimensional turbulent flow by large-scale machine learning by Ando, Kazuto, Onishi, Keiji, Bale, Rahul, Kuroda, Akiyoshi, Tsubokura, Makoto

“…A large-scale machine learning-based nonlinear reduced-order modeling method was developed for a three-dimensional turbulent flow field (Re=1000) using a…”
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Ultrasonic Weld Quality Inspection Involving Strength Prediction and Defect Detection in Data-Constrained Training Environments by Mohandas, Reenu, Mongan, Patrick, Hayes, Martin

“…Welding is an extensively used technique in manufacturing, and as for every other process, there is the potential for defects in the weld joint that could be…”
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Unsupervised VSP up- and downgoing wavefield separation via dual convolutional autoencoders by Lu, Cai, Mu, Zuochen, Zong, Jingjing, Wang, Tengyu

“…Vertical seismic profiling (VSP) is widely applied in the field of seismic exploration to deliver high-quality subsurface images and enable quantitative…”
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