Výsledky vyhledávání - "(conditional OR conditioning) variational (autoencoder（cvae）" OR autoencoder（cae）")

CNN and Convolutional Autoencoder (CAE) based real-time sensor fault detection, localization, and correction Autor 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 Autor 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 Autor 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 Autor 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 Autor 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 Autor 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 Autor 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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Deep Coupling Autoencoder for Fault Diagnosis With Multimodal Sensory Data Autor Ma, Meng, Sun, Chuang, Chen, Xuefeng

“…Effective fault diagnosis of rotating machinery has multifarious benefits, such as improved safety, enhanced reliability, and reduced maintenance cost, for…”
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FedRUL: A New Federated Learning Method for Edge-Cloud Collaboration Based Remaining Useful Life Prediction of Machines Autor 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 Autor 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 Autor 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 Autor 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 Autor 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 Autor 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 Autor 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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Causal Adversarial Autoencoder for Disentangled SAR Image Representation and Few-Shot Target Recognition Autor Guo, Qian, Xu, Huilin, Xu, Feng

“…Lack of interpretability and weak generalization ability have become the major challenges with data-driven intelligent SAR-ATR technology, especially in…”
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Unsupervised Change Detection Using Convolutional-Autoencoder Multiresolution Features Autor 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 Autor 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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Pilots' Fatigue Status Recognition Using Deep Contractive Autoencoder Network Autor Wu, Edmond Q., Peng, X. Y., Zhang, Caizhi Z., Lin, J. X., Sheng, Richard S. F.

“…The evaluation of pilots' fatigue status is of substantial significance in aviation safety, which faces two major issues. They are how to get the fatigue…”
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Unsupervised Hyperspectral Image Band Selection Based on Deep Subspace Clustering Autor 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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