Search Results - Encoder-decoder LSTM neural network

New encoder–decoder convolutional LSTM neural network architectures for next-day global ionosphere maps forecast

Authors: M. C. M. de Paulo H. A. Marques R. Q. Feitosa et al.

Source: GPS Solutions. 27

Regional Ship Collision Risk Prediction: An Approach Based On Encoder-Decoder Lstm Neural Network Model

Authors: Chenyan Lin Rong Zhen Yanting Tong et al.

Multi-Ship Collision Risk Prediction: An Approach Based on Encoder-Decoder Lstm Neural Network Combination Model

Authors: Chenyan Lin Rong Zhen Yanting Tong et al.

Regional ship collision risk prediction: An approach based on encoder-decoder LSTM neural network model

Authors: Chenyan Lin Rong Zhen Yanting Tong et al.

Source: Ocean Engineering. 296:117019

TRAFFIC ANOMALY DETECTION IN VEHICLE BUS BY RECURRENT LSTM NEURAL NETWORK

Source: Infokommunikacionnye tehnologii. :12-18

Image captioning using bidirectional LSTM neural network.

Authors: Hoseini, Farnaz Notash, Anaram Yaghoobi

Source: Discover Artificial Intelligence; 5/29/2025, Vol. 5 Issue 1, p1-22, 22p

Subject Terms: IMAGE processing, ARTIFICIAL neural networks, COMPUTER performance, PHOTOGRAPH captions, NEURAL computers

A generic LSTM neural network architecture to infer heterogeneous model transformations

Authors: Sébastien Gérard Jordi Cabot Loli Burgueño et al.

Contributors: Sébastien Gérard Jordi Cabot Loli Burgueño et al.

Source: RIUMA. Repositorio Institucional de la Universidad de Málaga
Universidad de Málaga

Subject Terms: [INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI], Artificial intelligence, 4. Education, 02 engineering and technology, 7. Clean energy, Model transformation, Redes neuronales (Informática), 13. Climate action, Arquitectura de ordenadores, Machine learning, 0202 electrical engineering, electronic engineering, information engineering, Code generation, 14. Life underwater, Model manipulation, Neural networks

Access URL: https://hdl.handle.net/10630/27636
https://link.springer.com/article/10.1007/s10270-021-00893-y
https://cea.hal.science/cea-04483974v1
https://doi.org/10.1007/s10270-021-00893-y

High- accuracy chaotic time series prediction of the flexible beam-ring model based on P_CNN-BiLSTM ED network.

Authors: Liu, Xinchang Sun, Ying Wang, Aiwen et al.

Source: European Physical Journal: Special Topics; Jun2025, Vol. 234 Issue 3, p603-618, 16p

Subject Terms: CONVOLUTIONAL neural networks, ARTIFICIAL neural networks, LONG short-term memory, TIME series analysis, NONLINEAR systems

Reservoir production capacity prediction of Zananor field based on LSTM neural network.

Authors: Liu, JiYuan Wang, Fei Zhang, ChengEn et al.

Source: Acta Geophysica; Feb2025, Vol. 73 Issue 1, p295-310, 16p

Subject Terms: ARTIFICIAL neural networks, LONG short-term memory, PRINCIPAL components analysis, ARTIFICIAL intelligence, FEATURE selection, RECURRENT neural networks

Robust electroencephalogram-based biometric identification against GAN-generated artificial signals using a novel end-to-end attention-based CNN-LSTM neural network.

Authors: Zarean, Javad Tajally, AmirReza Tavakkoli-Moghaddam, Reza et al.

Source: Cluster Computing; Jun2025, Vol. 28 Issue 3, p1-20, 20p

Subject Terms: GENERATIVE adversarial networks, BIOMETRIC identification, CONVOLUTIONAL neural networks, DEEP learning, MOTOR imagery (Cognition)

Research on Personalized Exercise Volume Optimization in College Basketball Training Based on LSTM Neural Network with Multi-Modal Data Fusion Intervention.

Authors: Lv, Xiongce Tao, Ye Xue, Yang

Source: Applied Sciences (2076-3417); Aug2025, Vol. 15 Issue 16, p8871, 12p

Subject Terms: BASKETBALL training, LONG short-term memory, DYNAMIC models, PHYSICAL education, BIOTELEMETRY, MULTISENSOR data fusion, KINEMATICS

New encoder–decoder convolutional LSTM neural network architectures for next-day global ionosphere maps forecast.

Authors: de Paulo, M. C. M. Marques, H. A. Feitosa, R. Q. et al.

Source: GPS Solutions; Apr2023, Vol. 27 Issue 2, p1-13, 13p

Multi-Scale Convolutional Vehicle Trajectory Prediction Integrating Spatiotemporal Attention Mechanism

Authors: YAN Jianhong, LIU Zhiyan, WANG Zhen

Source: Jisuanji gongcheng, Vol 51, Iss 8, Pp 406-414 (2025)

Subject Terms: multi-scale convolutional social pooling, trajectory prediction, long short-term memory (lstm) neural network, spatial-temporal attention mechanism, multi-scale feature fusion, Computer engineering. Computer hardware, TK7885-7895, Computer software, QA76.75-76.765

File Description: electronic resource

Relation: https://www.ecice06.com/fileup/1000-3428/PDF/jsjgc-51-8-406.pdf; https://doaj.org/toc/1000-3428

Access URL: https://doaj.org/article/e01ac5ba8e024e7185558e24be16fd4c

A roll attitude determination method based on the jamming energy of GEO satellites and an LSTM neural network.

Authors: Li, Rundong Feng, Lu Wu, Peng et al.

Source: Scientific Reports; 5/23/2025, Vol. 15 Issue 1, p1-19, 19p

Subject Terms: LONG short-term memory, GLOBAL Positioning System, ATTITUDE testing, COMMONS, ORBITS (Astronomy), ARTIFICIAL satellite attitude control systems, GEOSTATIONARY satellites

Deep learning time-series modeling for assessing land subsidence under reduced groundwater use.

Authors: Liu, Chih-Yu Ku, Cheng-Yu Ni, Chuen‑Fa

Source: Scientific Reports; 8/22/2025, Vol. 15 Issue 1, p1-22, 22p

Subject Terms: LAND subsidence, GROUNDWATER, RECURRENT neural networks, ENVIRONMENTAL remediation, DEEP learning, PREDICTION models

Geographic Terms: TAIWAN

A Deep Learning Model for Smart Manufacturing Using Convolutional LSTM Neural Network Autoencoders

Authors: Aniekan Essien Cinzia Giannetti

Source: IEEE Transactions on Industrial Informatics. 16:6069-6078

Subject Terms: 0209 industrial biotechnology, 9. Industry and infrastructure, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Access URL: https://ieeexplore.ieee.org/ielx7/9424/9106618/08967003.pdf
https://cronfa.swan.ac.uk/Record/cronfa53318
https://dblp.uni-trier.de/db/journals/tii/tii16.html#EssienG20
https://cronfa.swan.ac.uk/Record/cronfa53318/Download/53318__17414__2da379d11c2f437aa113e87ad1ed306b.pdf
https://ieeexplore.ieee.org/iel7/9424/9106618/08967003.pdf
https://ieeexplore.ieee.org/abstract/document/8967003/
https://cronfa.swan.ac.uk/Record/cronfa53318/Download/53318__17414__2da379d11c2f437aa113e87ad1ed306b.pdf

Hybrid Architecture using CNN and LSTM for Image Captioning in Hindi Language.

Authors: Poddar, Ayush Kumar Rani, Dr. Rajneesh

Source: Procedia Computer Science. 2023, Vol. 218, p686-696. 11p.

Subject Terms: Hindi language, Natural language processing, Computer vision, Deep learning, Machine learning, Recurrent neural networks

Design and Implementation of an Intelligent Web Service Agent Based on Seq2Seq and Website Crawler.

Authors: Hsih, Mei-Hua Yang, Jian-Xin Hsieh, Chen-Chiung

Source: Information. Dec2024, Vol. 15 Issue 12, p818. 19p.

Subject Terms: *Artificial neural networks, *Natural language processing, *Internet content, *Web services, Online social networks, Intelligent personal assistants

Image captioning deep learning model using ResNet50 encoder and hybrid LSTM–GRU decoder optimized with beam search.

Authors: Kavitha, P. V. Karpagam, V.

Source: Automatika: Journal for Control, Measurement, Electronics, Computing & Communications. Aug2025, Vol. 66 Issue 3, p394-410. 17p.

Subject Terms: Natural language processing, Convolutional neural networks, Language models, Computer vision, Feature extraction

A generic LSTM neural network architecture to infer heterogeneous model transformations.

Authors: Burgueño-Caballero, Lola Cabot, Jordi Li, Shuai et al.

Subject Terms: Arquitectura de ordenadores, Redes neuronales (Informática), Model manipulation, Code generation, Model transformation, Artificial intelligence, Machine learning, Neural networks

Relation: XXVII Jornadas de Ingeniería del Software y Bases de Datos (JISBD 2023); Ciudad Real, España; 12/09/2023-14/09/2023; https://hdl.handle.net/10630/27636

Availability: https://hdl.handle.net/10630/27636