Search Results - spatial and temporal autoencoder

Stacked Spatial-Temporal Autoencoder for Quality Prediction in Industrial Processes by Yan, Feng, Yang, Chunjie, Zhang, Xinmin

“… Therefore, in this paper, a stacked spatial-temporal autoencoder (S 2 TAE) is proposed to enhance the representation learning capability for soft sensor modeling by taking the spatial-temporal correlations into consideration…”
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Batch process quality prediction based on denoising autoencoder-spatial temporal convolutional attention mechanism fusion network: Batch process quality prediction based on denoising autoencoder-spatial temporal convolutional attention mechanism fusion network by Zhang, Yan, Cao, Jie, Zhao, Xiaoqiang, Hui, Yongyong

“… to prediction performance. Therefore, a denoising autoencoder-Spatial Temporal Convolution Attention Fusion Network (DAE-STCAFN…”
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Efficient identification of Alzheimer’s brain dynamics with Spatial-Temporal Autoencoder: A deep learning approach for diagnosing brain disorders by Wu, Lingyun, Zhao, Quanfa, Liu, Jing, Yu, Haitao

“…•A Spatial-Temporal Autoencoder (STAE) framework was designed to estimate latent factors of EEG via unsupervised learning…”
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A novel spatial–temporal generative autoencoder for wind speed uncertainty forecasting by Ma, Long, Huang, Ling, Shi, Huifeng

“…–temporal correlation between wind turbines. In this paper, based on variational Bayesian inference, we propose a novel spatial…”
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Multivariate time series anomaly detection with variational autoencoder and spatial–temporal graph network by Guan, Siwei, He, Zhiwei, Ma, Shenhui, Gao, Mingyu

“…–temporal graph networks and variational autoencoder (VAE). It employs…”
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Parallel Symmetric Appearance‐Motion Framework With Diffusion and Refinement Blocks for Video Anomaly Detection System by Prasad, Kavitapu Naga Siva Shankara Vara, Haritha, Dasari

“… Spatial and temporal Residual Inception‐based autoencoder extracts multi‐level features and optical flow maps in video frames…”
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Multi-modal hybrid modeling strategy based on Gaussian Mixture Variational Autoencoder and spatial–temporal attention: Application to industrial process prediction by Peng, Haifei, Long, Jian, Huang, Cheng, Wei, Shibo, Ye, Zhencheng

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Spatial–Temporal Heatmap Masked Autoencoder for Skeleton-Based Action Recognition by Bian, Cunling, Yang, Yang, Wang, Tao, Lu, Weigang

“… In this work, we propose the Spatial–Temporal Heatmap Masked Autoencoder (STH-MAE), a novel self-supervised framework tailored for skeleton-based action recognition…”
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Distributed temporal–spatial neighbourhood enhanced variational autoencoder for multiunit industrial plant‐wide process monitoring by Yao, Zongyu, Jiang, Qingchao, Gu, Xingsheng, Pan, Chunjian

“… In this paper, a novel distributed temporal–spatial neighbourhood enhanced variational autoencoder (DTS‐VAE…”
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Network traffic classification using deep convolutional recurrent autoencoder neural networks for spatial–temporal features extraction by D’Angelo, Gianni, Palmieri, Francesco

“… For this purpose, a novel autoencoder-based deep neural network architecture…”
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A Spatial-Temporal Variational Graph Attention Autoencoder Using Interactive Information for Fault Detection in Complex Industrial Processes by Lv, Mingjie, Li, Yonggang, Liang, Huiping, Sun, Bei, Yang, Chunhua, Gui, Weihua

“… A spatial-temporal variational graph attention autoencoder (STVGATE) using interactive information is proposed for fault detection, which aims to effectively capture the spatial and temporal features of the interconnected…”
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Spatial-Temporal Cascade Autoencoder for Video Anomaly Detection in Crowded Scenes by Li, Nanjun, Chang, Faliang, Liu, Chunsheng

“…". In this paper, we propose a cuboid-patch-based method characterized by a cascade of classifiers called a spatial-temporal cascade autoencoder (ST-CaAE…”
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Robust Spatial-Temporal Autoencoder for Unsupervised Anomaly Detection of Unmanned Aerial Vehicle With Flight Data by Jiang, Guoqian, Nan, Pengcheng, Zhang, Jingchao, Li, Yingwei, Li, Xiaoli

“… Specifically, we designed a new robust spatial-temporal autoencoder (RSTAE) model based on the temporal convolution network (TCN…”
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Masked Autoencoders for Spatial-Temporal Relationship in Video-Based Group Activity Recognition by Yadav, Rajeshwar, Halder, Raju, Banda, Gourinath

“… Previous methods, however, either feature a complex framework requiring individual action labels or need more adequate modelling of spatial and temporal features…”
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Adaptive Temporal–Spatial Pyramid Variational Autoencoder Model for Multirate Dynamic Chemical Process Soft Sensing Application by Shen, Bingbing, Yang, Zeyu, Yao, Le

“… This paper innovatively proposes a temporal–spatial pyramid variational autoencoder (TS-PVAE) model for the nonlinear temporal…”
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STAR: A Spatial-Temporal Autoencoder for EEG Restoration in Emotion Recognition by Yin, Hao-Long, Zheng, Wei-Long, Lu, Bao-Liang

“… To overcome these challenges, we introduce the Spatial-Temporal Autoencoder for EEG Restoration (STAR…”
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Trust-aware denoising autoencoder with spatial-temporal activity for cross-domain personalized recommendations by Ahmed, Adeel, Saleem, Khalid, Khalid, Osman, Gao, Jiechao, Rashid, Umer

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Threat Detection Framework for IoT Devices Using Adaptive Dilated Conv‐Gated Recurrent Units With Spatial and Temporal Attention‐Based Residual Autoencoder by Shirode, Ujwal Ramesh, Vhatkar, Kapil Netaji, Sontakke, Prakash V., Pawar, Aarti S., Salunke, Dipmala

“…ABSTRACT Purpose Internet of Things (IoT) network is equipped with sensors, actuators, and act as communication capabilities. It enables device to collect,…”
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Multimodal Multi-View Spectral-Spatial-Temporal Masked Autoencoder for Self-Supervised Emotion Recognition by Gao, Pengxuan, Liu, Tianyu, Liu, Jia-Wen, Lu, Bao-Liang, Zheng, Wei-Long

“… In this paper, we propose a Multimodal Multi-view Spectral-Spatial-Temporal Masked Autoencoder (Multimodal MV-SSTMA…”
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TASA: Temporal Attention With Spatial Autoencoder Network for Odor-Induced Emotion Classification Using EEG by Tong, Chengxuan, Ding, Yi, Zhang, Zhuo, Zhang, Haihong, JunLiang Lim, Kevin, Guan, Cuntai

“… In this paper, we propose a deep learning architecture called Temporal Attention with Spatial Autoencoder Network (TASA…”
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