Suchergebnisse - Encoder-decoder LSTM neural network

New encoder–decoder convolutional LSTM neural network architectures for next-day global ionosphere maps forecast von de Paulo, M. C. M., Marques, H. A., Feitosa, R. Q., Ferreira, M. P.

“… ). Here, we propose convolutional recurrent neural network architectures to forecast VTEC based on global ionosphere maps (GIMs …”
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Regional ship collision risk prediction: An approach based on encoder-decoder LSTM neural network model von Lin, Chenyan, Zhen, Rong, Tong, Yanting, Yang, Shenhua, Chen, Shengkai

“… In order to solve the problem of ship collision risk prediction, this study proposes a regional ship collision risk prediction model based on the Encoder-decoder LSTM neural network …”
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Towards CSI-based diversity activity recognition via LSTM-CNN encoder-decoder neural network von Guo, Linlin, Zhang, Hang, Wang, Chao, Guo, Weiyu, Diao, Guangqiang, Lu, Bingxian, Lin, Chuang, Wang, Lei

“… Based on this, we design a novel deep learning model called LCED which consists of one LSTM-based Encoder, features image presentation, and one CNN-based Decoder to weaken the accuracy differences …”
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Investigation of different LSTM-based encoder-decoder neural networks for vehicle speed prediction von Heckelmann, Paul, Breuer, Sandro Chris, Rinderknecht, Stephan

“… In this work, different Long Short-Term Memory (LSTM) encoder-decoder artificial neural networks are investigated …”
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Recurrent and convolutional neural networks in structural dynamics: a modified attention steered encoder–decoder architecture versus LSTM versus GRU versus TCN topologies to predict the response of shock wave-loaded plates von Tandale, Saurabh Balkrishna, Stoffel, Marcus

“… The aim of the present study is to analyse and predict the structural deformations occurring during shock tube experiments with a series of recurrent and temporal convolutional neural networks …”
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A novel Encoder-Decoder model based on read-first LSTM for air pollutant prediction von Zhang, Bo, Zou, Guojian, Qin, Dongming, Lu, Yunjie, Jin, Yupeng, Wang, Hui

“… A prevalent recent approach to time series prediction is the Encoder-Decoder model, which is based on recurrent neural networks (RNN …”
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A CNN encoder decoder LSTM model for sustainable wind power predictive analytics von Garg, Sherry, Krishnamurthi, Rajalakshmi

“… Long Short-Term Memory (LSTM) involves prediction using temporal relationships of data points collected over a period of time …”
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Intelligent Tracking of Mechanically Thrown Objects by Industrial Catching Robot for Automated In-Plant Logistics 4.0 von Qadeer, Nauman, Shah, Jamal Hussain, Sharif, Muhammad, Khan, Muhammad Attique, Muhammad, Ghulam, Zhang, Yu-Dong

“… Industry 4.0 smart manufacturing systems are equipped with sensors, smart machines, and intelligent robots. The automated in-plant transportation of …”
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Neural Network as Datasheet: Modeling B-H Loops of Power Magnetics with Sequence-to-Sequence LSTM Encoder-Decoder Architecture von Serrano, Diego, Li, Haoran, Guillod, Thomas, Wang, Shukai, Luo, Min, Sullivan, Charles R., Chen, Minjie

“… This paper presents the concept of "Neural Network as Datasheet" for B- H loop modeling of power magnetics with sequence-to-sequence machine learning …”
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A batch-wise LSTM-encoder decoder network for batch process monitoring von Ren, Jiayang, Ni, Dong

“… In this work, a multi-layer recurrent neural network in the encoder–decoder structure called batch-wise LSTM-encoder decoder network is proposed to solve the difficulties …”
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Condition assessment and predictive maintenance for contact probe using health index and encoder‐decoder LSTM model von Luk, Shun‐Sun, Jin, Yanwen, Zhang, Xiaoge, Ng, Vincent To‐Yee, Huang, Jingyuan, Wong, Chak‐Nam

“… Contact probe is broadly used for the continuous monitoring of microelectronic components in manufacturing industries. False rejection of fine product due to …”
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Accurate water quality prediction with attention-based bidirectional LSTM and encoder–decoder von Bi, Jing, Chen, Zexian, Yuan, Haitao, Zhang, Jia

“… , Long Short-Term Memory (LSTM) and encoder–decoder, have been widely used to predict time series data …”
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Image Captioning Encoder–Decoder Models Using CNN-RNN Architectures: A Comparative Study von Suresh, K. Revati, Jarapala, Arun, Sudeep, P. V.

“… The NIC generator combines a convolutional neural network (CNN) encoder and a long short-term memory (LSTM) decoder …”
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Development of a TVF-EMD-based multi-decomposition technique integrated with Encoder-Decoder-Bidirectional-LSTM for monthly rainfall forecasting von Jamei, Mehdi, Ali, Mumtaz, Malik, Anurag, Karbasi, Masoud, Rai, Priya, Yaseen, Zaher Mundher

“… •Monthly scale of rainfall is forecasted at the Himalaya region of India.•Novel intelligence machine learning model is proposed for this purpose.•Data time …”
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Trace2trace—A Feasibility Study on Neural Machine Translation Applied to Human Motion Trajectories von Crivellari, Alessandro, Beinat, Euro

“… Neural machine translation is a prominent field in the computational linguistics domain …”
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A signal recovery method for bridge monitoring system using TVFEMD and encoder-decoder aided LSTM von Xin, Jingzhou, Zhou, Chaoying, Jiang, Yan, Tang, Qizhi, Yang, Xianyi, Zhou, Jianting

“… To settle this problem, this paper proposes a method for the recovery of bridge monitoring data based on the combination of the time varying filtering based empirical mode decomposition (TVFEMD), encoder-decoder (ED …”
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Advanced Intelligent Control in Robots

“… ) and intelligent communication including remote control, adaptive sensor networks and human–robot (H2R …”
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Predicting the performance of hybrid ventilation in buildings using a multivariate attention-based biLSTM Encoder – Decoder von Chaudhary, Gaurav, Johra, Hicham, Georges, Laurent, Austbø, Bjørn

“… ) encoder-decoder neural network …”
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Prediction of maize growth stages based on deep learning von Yue, Yang, Li, Jin-Hai, Fan, Li-Feng, Zhang, Li-Li, Zhao, Peng-Fei, Zhou, Qiao, Wang, Nan, Wang, Zhong-Yi, Huang, Lan, Dong, Xue-Hui

“… •ConvLSTM encoder-decoder model can forecast daily weather factors correctly.•Hybrid model and data-driven model can predict maize growth stages …”
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Improving Stockline Detection of Radar Sensor Array Systems in Blast Furnaces Using a Novel Encoder–Decoder Architecture von Liu, Xiaopeng, Liu, Yan, Zhang, Meng, Chen, Xianzhong, Li, Jiangyun

“… In this paper, a novel encoder–decoder architecture that consists of a convolution neural network (CNN …”
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