Search Results - "(conditional OR conditioning) variational (autoencoder(cave)*" OR 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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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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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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Context Autoencoder for Self-supervised Representation Learning by Chen, Xiaokang, Ding, Mingyu, Wang, Xiaodi, Xin, Ying, Mo, Shentong, Wang, Yunhao, Han, Shumin, Luo, Ping, Zeng, Gang, Wang, Jingdong

“…We present a novel masked image modeling (MIM) approach, context autoencoder (CAE), for self-supervised representation pretraining…”
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Pilots' Fatigue Status Recognition Using Deep Contractive Autoencoder Network by 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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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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Deep Coupling Autoencoder for Fault Diagnosis With Multimodal Sensory Data by Ma, Meng, Sun, Chuang, Chen, Xuefeng

“… The present study proposes a deep coupling autoencoder (DCAE) model that handles the multimodal sensory signals not residing in a commensurate space, such as vibration…”
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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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CAE-CNN: Predicting transcription factor binding site with convolutional autoencoder and convolutional neural network by Zhang, Yongqing, Qiao, Shaojie, Zeng, Yuanqi, Gao, Dongrui, Han, Nan, Zhou, Jiliu

“…•CAE-CNN share the parameters, so the training time can be significantly reduced.•Effectively gradient-based training the model by the gating units…”
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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 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 fNIRS feature extraction with CAE and ESN autoencoder for driver cognitive load classification by Liu, Ruixue, Reimer, Bryan, Song, Siyang, Mehler, Bruce, Solovey, Erin

“… To classify different driver cognitive load levels, we examined the application of convolutional autoencoder (CAE…”
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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

“…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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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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Causal Adversarial Autoencoder for Disentangled SAR Image Representation and Few-Shot Target Recognition by Guo, Qian, Xu, Huilin, Xu, Feng

“… A Causal Adversarial auto-Encoder (CAE) for SAR-ATR is then proposed to embody this disentangled representation, which incorporates a number of novel built-in network features…”
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A Novel Convolutional Autoencoder-Based Clutter Removal Method for Buried Threat Detection in Ground-Penetrating Radar by Temlioglu, Eyyup, Erer, Isin

“… A new clutter removal method based on convolutional autoencoders (CAEs) is introduced. The raw GPR image is encoded via successive convolution and pooling layers and then decoded to provide the clutter-free GPR image…”
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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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Autoencoder-based network anomaly detection by Chen, Zhaomin, Yeo, Chai Kiat, Lee, Bu Sung, Lau, Chiew Tong

“… We also apply the Convolutional Autoencoder (CAE) here to perform the dimensionality reduction…”
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