Výsledky vyhľadávania - convolutional LSTM autoencoder

ConvAE-LSTM: Convolutional Autoencoder Long Short-Term Memory Network for Smartphone-Based Human Activity Recognition Autor Thakur, Dipanwita, Biswas, Suparna, Ho, Edmond S. L., Chattopadhyay, Samiran

“…, accelerometer and gyroscope data. Convolutional neural networks (CNNs), autoencoders (AEs), and long short-term memory (LSTM…”
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The Prediction of the Remaining Useful Life of Rotating Machinery Based on an Adaptive Maximum Second-Order Cyclostationarity Blind Deconvolution and a Convolutional LSTM Autoencoder Autor Gao, Yangde, Ahmad, Zahoor, Kim, Jong-Myon

“…) and a convolutional LSTM autoencoder to achieve the feature extraction, health index analysis, and RUL prediction for rotating machinery…”
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A Deep Learning Model for Smart Manufacturing Using Convolutional LSTM Neural Network Autoencoders Autor Essien, Aniekan, Giannetti, Cinzia

“… The model comprises a deep convolutional…”
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Hybrid convolutional Bi-LSTM autoencoder framework for short-term wind speed prediction Autor Kosana, Vishalteja, Teeparthi, Kiran, Madasthu, Santhosh

“… Encoder and decoder are the two parts of the proposed hybrid model. In this study, a one-dimensional convolutional neural network (1D-CNN…”
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Prediction of Ocean Weather Based on Denoising AutoEncoder and Convolutional LSTM Autor Kim, Ki-Su, Lee, June-Beom, Roh, Myung-Il, Han, Ki-Min, Lee, Gap-Heon

“…The path planning of a ship requires much information, and one of the essential factors is predicting the ocean environment. Ocean weather can generally be…”
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Watershed groundwater level multistep ahead forecasts by fusing convolutional-based autoencoder and LSTM models Autor Kow, Pu-Yun, Liou, Jia-Yi, Sun, Wei, Chang, Li-Chiu, Chang, Fi-John

“… This study proposed a novel ConvAE-LSTM model, which fused a Convolutional-based Autoencoder model (ConvAE…”
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Semantic Segmentation of SLAR Imagery with Convolutional LSTM Selectional AutoEncoders Autor Gallego, Antonio-Javier, Gil, Pablo, Pertusa, Antonio, Fisher, Robert B.

“… The proposed approach introduces a new type of neural architecture named Convolutional Long Short Term Memory Selectional AutoEncoders (CMSAE…”
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Distributed Convolutional Autoencoder and LSTM Model for Optimized MVNO Slicing in 6G Networks Autor Jain, Megha, Verma, Ravi, Amudhavel, J.

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A novel dimensionality reduction approach for ECG signal via convolutional denoising autoencoder with LSTM Autor Dasan, Evangelin, Panneerselvam, Ithayarani

“…•Compressing the signal before transmission can reduce the signal transmission cost in wearable technology.•Reduced transmission time can increase the battery…”
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Multistage Convolutional Autoencoder and BCM-LSTM Networks for RUL Prediction of Rolling Bearings Autor Wang, Zhaozong, Cheng, Jiangfeng, Zheng, Hui, Zou, Xiaofu, Tao, Fei

“… This article presents a rolling bearing RUL prediction method based on multistage convolutional autoencoder (MSCAE…”
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Fall Detection of the Elderly Using Denoising LSTM-Based Convolutional Variant Autoencoder Autor Yi, Myung-Kyu, Han, Kyunghyun, Hwang, Seong Oun

“…)-based convolutional variational autoencoder (CVAE) model to solve the problem of lack of fall data…”
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Enhancing Video Anomaly Detection Using Spatio-Temporal Autoencoders and Convolutional LSTM Networks Autor Almahadin, Ghayth, Subburaj, Maheswari, Hiari, Mohammad, Sathasivam Singaram, Saranya, Kolla, Bhanu Prakash, Dadheech, Pankaj, Vibhute, Amol D., Sengan, Sudhakar

“…Identifying suspicious activities or behaviors is essential in the domain of Anomaly Detection (AD). In crowded scenes, the presence of inter-object occlusions…”
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Novel Soft Smart Shoes for Motion Intent Learning of Lower Limbs Using LSTM With a Convolutional Autoencoder Autor Yang, Jiantao, Yin, Yuehong

“… This study presents novel soft smart shoes designed for motion intent learning at unspecified walking speeds using long short-term memory with a convolutional autoencoder…”
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Air Traffic Prediction as a Video Prediction Problem Using Convolutional LSTM and Autoencoder Autor Kim, Hyewook, Lee, Keumjin

“… An autoencoder with convolutional long short-term memory (ConvLSTM) is used, and a mixed loss function technique is proposed to generate better air traffic images than those obtained by using conventional L1 or L2 loss function…”
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Optimizing dotted Arabic expiration date recognition with ARABEX: a convolutional autoencoder with bidirectional LSTM and CRNN approach Autor Zaki, Hozaifa, Soliman, Ghada

“…In this study, we introduced an approach for Automated Dotted Arabic Expiration Date Extraction using an Optimized Convolutional Autoencoder with a bidirectional LSTM…”
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Enhanced Intelligent Video Monitoring using Hybrid Integration of Spatiotemporal Autoencoders and Convolutional LSTMs Autor Umale-Nagmote, Ankita, Goel, Charu, Lal, Nidhi

“… This paper proposes a hybrid deep learning framework that combines spatial-temporal autoencoders with convolutional LSTMs for automated anomaly detection in surveillance videos…”
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Enhanced Intelligent Video Monitoring using Hybrid Integration of Spatiotemporal Autoencoders and Convolutional LSTMs Autor Umale-Nagmote, Ankita, Goel, Charu, Lal, Nidhi

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A deep learning approach for error detection and quantification in extrusion-based bioprinting Autor Bonatti, Amedeo Franco, Vozzi, Giovanni, Kai Chua, Chee, De Maria, Carmelo

“… features from a training dataset and generalize to new, unseen data. In this work, we present a novel application of a deep learning model to EBB, namely a convolutional Long Short-Term Memory (LSTM…”
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FA-SconvAE-LSTM: Feature-Aligned Stacked Convolutional Autoencoder with Long Short-Term Memory Network for Soft Sensor Modeling Autor Wu, Ping, Miao, Zengdi, Wang, Ke, Gao, Jinfeng, Zhang, Xujie, Lou, Siwei, Yang, Chunjie

“… In this study, a spatio-temporal model, termed the feature-aligned stacked convolutional autoencoder with long short-term memory, is proposed to develop soft sensors for nonlinear dynamic industrial processes…”
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Abnormal Event Detection in Videos using LSTM Convolutional Autoencoder Autor Berroukham, Abdelhafid, Housni, Khalid, Lahraichi, Mohammed

“…This research investigates the application of a novel LSTM Convolutional Autoencoder (LSTM-CAE…”
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