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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CAE-MAS: Convolutional Autoencoder Interference Cancellation for Multiperson Activity Sensing With FMCW Microwave Radar by Raeis, Hossein, Kazemi, Mohammad, Shirmohammadi, Shervin

“…’ limitation of detecting single human activities. To this end, a range–Doppler map of the data is extracted with an FWCW radar, and the interference effect of this map is mitigated by a convolutional…”
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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

“… In this article, a new DNN, one-dimensional residual convolutional autoencoder (1-DRCAE), is proposed for learning features from vibration signals directly in an unsupervised-learning way…”
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CAE-MAS: Convolutional Autoencoder Interference Cancellation for Multi-Person Activity Sensing with FMCW Microwave Radar by Raeis, Hossein, Kazemi, Mohammad, Shirmohammadi, Shervin

“… To this end, a range-doppler map of the data is extracted with a FWCW radar, and the interference effect of this map is mitigated by a Convolutional…”
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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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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…”
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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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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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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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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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XChange: An Explainable Dynamic Convolutional Autoencoder for Unsupervised Change Detection by Bergamasco, Luca, Bovolo, Francesca

“…Explainable artificial intelligence (XAI) approaches started to be studied in the last period to improve the interpretability of increasingly complex deep…”
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Robust Sensor Fault Detection in Wireless Sensor Networks Using a Hybrid Conditional Generative Adversarial Networks and Convolutional Autoencoder by Khan, Rehan, Saeed, Umer, Koo, Insoo

“…In the rapidly growing realm of the Internet of Things (IoT), reliance on sensor-generated data has become crucial for the operation of multiple services and…”
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Unsupervised VSP up- and downgoing wavefield separation via dual convolutional autoencoders by Lu, Cai, Mu, Zuochen, Zong, Jingjing, Wang, Tengyu

“… Inspired by that, we propose an unsupervised VSP wavefield separation framework via dual convolutional autoencoders named dualCAE…”
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Lamb Wave Dispersion Compensation Based on a Fourier Basis Convolutional Autoencoder by Li, Shuaiyong, Yang, Zhang, Zeng, Jianxin

“…The inherent dispersion of Lamb waves will reduce the signal-to-noise ratio (SNR) and detection sensitivity of the detection signal, seriously affecting the…”
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Electrocardiogram Signal Compression Using Deep Convolutional Autoencoder with Constant Error and Flexible Compression Rate by Bekiryazıcı, Tahir, Aydemir, Gürkan, Gürkan, Hakan

“…Objectives Electrocardiogram (ECG) signals are beneficial for diagnosing cardiac diseases. The cardiac patients' life quality likely increases with continuous…”
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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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An Improved Data Compression Framework for Wireless Sensor Networks Using Stacked Convolutional Autoencoder (S-CAE) by Kumble, Lithin, Patil, Kiran Kumari

“… We introduce a stacked convolutional RBM auto-encoder (stacked CAE) model for compressing sensor data, which is made up of layers…”
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