Search Results - "lstm autoencoder"

Enhancing Weather Monitoring for Agriculture with Deep Learning: Anomaly Detection in East Java Using LSTM Autoencoder and OCSVM

Authors: Maulana Ahsan Fadillah Yenni Angraini Rahma Anisa

Source: JOIN: Jurnal Online Informatika, Vol 10, Iss 1, Pp 227-238 (2025)

Subject Terms: ocsvm, weather, Electronic computers. Computer science, QA75.5-76.95, lstm autoencoder, lstm, anomaly detection

Access URL: https://doaj.org/article/40bb9600e82a47f0a6decd94607ceb8a

BIM log mining framework using deep learning for productivity assessment in construction facilities

Authors: Ali Akbar Younghee Chang Jinwoo Song et al.

Source: Journal of Asian Architecture and Building Engineering, Vol 0, Iss 0, Pp 1-16 (2025)

Subject Terms: deep learning architectures, Building construction, building information modeling (bim), construction productivity, Architecture, bim log mining, lstm autoencoder, NA1-9428, TH1-9745

Access URL: https://doaj.org/article/db43ee25bcf44a55b8732a20c2a2ba75

A deep semi-supervised machine learning algorithm for detecting transportation modes based on GPS tracking data

Authors: Sadeghian, Paria Golshan, Arman Zhao, Xiaoyun, Ph.D. et al.

Source: Transportation.

Subject Terms: Travel identification, LSTM Autoencoder, Unsupervised learning, Deep learning, GPS tracking data

File Description: electronic

Access URL: https://urn.kb.se/resolve?urn=urn:nbn:se:du-48203
https://doi.org/10.1007/s11116-024-10472-x

Federated Learning for Market Surveillance

Authors: Song, Philip Kanwal, Summrina Dashtipour, Kia et al.

Source: Decision Making and Security Risk Management for IoT Environments Advances in Information Security (ADIS). :199-218

Subject Terms: Anomaly detection, Federated learning, LSTM autoencoder, Machine learning, Market surveillance

File Description: print

Access URL: https://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-53022

A Two-Stage Framework for Fault and Cyber Attack Detection in Line Current Differential Relays of Power Transmission Network

Authors: Anfaj Islam Duy-Hung Ha Trung-Thang Nguyen et al.

Source: IEEE Access, Vol 13, Pp 195257-195271 (2025)

Subject Terms: Anomaly detection, cyberattack detection, fault detection, line current differential relay, LSTM-autoencoder, OPAL-RT simulation, Electrical engineering. Electronics. Nuclear engineering, TK1-9971

File Description: electronic resource

Relation: https://ieeexplore.ieee.org/document/11248810/; https://doaj.org/toc/2169-3536

Access URL: https://doaj.org/article/64e48e113d3b46d3a88e1a2ba01f42e5

Unsupervised anomaly detection in industrial machines supported by vibration analysis under data scarcity constraints

Authors: Torres, Pedro Spencer, Geoffrey Esteves, Arthur et al.

Contributors: Torres, Pedro Spencer, Geoffrey Esteves, Arthur et al.

Subject Terms: Condition monitoring, Anomaly detection, Vibration analysis, Unsupervised learning, Data scarcity, LSTM Autoencoder

File Description: application/pdf

Availability: http://hdl.handle.net/10400.11/10338

Sensor-Level Anomaly Detection in DC–DC Buck Converters with a Physics-Informed LSTM: DSP-Based Validation of Detection and a Simulation Study of CI-Guided Deception

Authors: Jeong-Hoon Moon Jin-Hong Kim Jung-Hwan Lee

Source: Applied Sciences, Vol 15, Iss 20, p 11112 (2025)

Subject Terms: physics-informed neural networks, LSTM autoencoder, anomaly detection, DC–DC buck converter, cyber-physical security, embedded DSP, Technology, Engineering (General). Civil engineering (General), TA1-2040, Biology (General), QH301-705.5, Physics, QC1-999, Chemistry, QD1-999

File Description: electronic resource

Relation: https://www.mdpi.com/2076-3417/15/20/11112; https://doaj.org/toc/2076-3417

Access URL: https://doaj.org/article/2b8cd62513274987b9025ebc84d8d80a

Fall Detection by Deep Learning-Based Bimodal Movement and Pose Sensing with Late Fusion

Authors: Haythem Rehouma Mounir Boukadoum

Source: Sensors, Vol 25, Iss 19, p 6035 (2025)

Subject Terms: fall detection, multimodal learning, LSTM autoencoder, Transformer, IMU, pose estimation, Chemical technology, TP1-1185

File Description: electronic resource

Relation: https://www.mdpi.com/1424-8220/25/19/6035; https://doaj.org/toc/1424-8220

Access URL: https://doaj.org/article/876990373f7f442f986102b6942c5f57

Deep Learning Autoencoder Study on ECG Signals

Authors: Dandi Mochamad Reza Satria Mandala Salim M. Zaki et al.

Source: Jurnal Nasional Teknik Elektro, Pp 82-88 (2023)

Subject Terms: autoencoder, deep lstm autoencoder, 0202 electrical engineering, electronic engineering, information engineering, deep learning, Electrical engineering. Electronics. Nuclear engineering, 02 engineering and technology, electrocardiogram, arrhythmia, 01 natural sciences, TK1-9971, 0104 chemical sciences

Access URL: https://doaj.org/article/dd399102940b4f358797433e7ba335d4

A Novel Autoencoders-LSTM Model for Stroke Outcome Prediction Using Multimodal MRI Data

Authors: Hatami, Nima Mechtouff, Laura Rousseau, David et al.

Contributors: Hatami, Nima Mechtouff, Laura Rousseau, David et al.

Source: 2023 IEEE 20th International Symposium on Biomedical Imaging (ISBI). :1-5

Subject Terms: [INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI], FOS: Computer and information sciences, Computer Science - Machine Learning, Multimodal image fusion, Computer Vision and Pattern Recognition (cs.CV), Magnetic Resonance Imaging (MRI), Computer Science - Computer Vision and Pattern Recognition, Stroke outcome prediction, Long Short-Term Memory (LSTM), Multimodal image fusion Long Short-Term Memory (LSTM) Autoencoder (AE) Stroke outcome prediction Magnetic Resonance Imaging (MRI) modified Rankin Scale (mRS), Machine Learning (cs.LG), modified Rankin Scale (mRS), [INFO.INFO-TI] Computer Science [cs]/Image Processing [eess.IV], Autoencoder (AE)

File Description: application/pdf

Access URL: http://arxiv.org/abs/2303.09484
https://hal.science/hal-04210499v1/document
https://hal.science/hal-04210499v1
https://doi.org/10.1109/isbi53787.2023.10230459

Estimation of frequency-dependent impedances in power grids by deep lstm autoencoder and random forest

Authors: Bagheri, Azam Bongiorno, Massimo Gu, Irene Yu-Hua et al.

Source: Energies. 14(13)

Subject Terms: Unsupervised deep learning, PRBS, Time-series analysis, Random forest regres-sion, Frequency-dependent grid impedance, LSTM autoencoder

File Description: electronic

Access URL: https://research.chalmers.se/publication/524893
https://research.chalmers.se/publication/524893/file/524893_Fulltext.pdf

Smart sensing and anomaly detection for microalgae culture based on LoRaWAN sensors and LSTM autoencoder

Authors: Soon, Chin Fhong Jamia’an, Mahdzir Mohamed Sunar, Norshuhaila et al.

Subject Terms: Internet of Things, LoRaWAN, Microalgae, Smart aquaculture, LSTM autoencoder, Anomaly detection

Availability: https://doi.org/10.1007/s10499-025-02104-7
https://napier-repository.worktribe.com/file/4622318/1/Smart%20sensing%20and%20anomaly%20detection%20for%20microalgae%20culture%20based%20on%20LoRaWAN%20sensors%20and%20LSTM%20autoencoder

Enhanced Wearable ECG Monitoring with LSTM Autoencoder-Based Anomaly Detection

Authors: Abbasi, Ali Raza Samra Aslam Saba Akram et al.

Source: Journal of Computers and Intelligent Systems; Vol. 3 No. 4 (2025): J. of Comp. & Int. Sys.; 244-255 ; 3007-3391

Subject Terms: Wearable Sensors, Anomaly Detection, LSTM Autoencoder, ECG, Machine Learning, Deep Learning

File Description: application/pdf

Relation: https://journals.iub.edu.pk/index.php/JCIS/article/view/4146/2189; https://journals.iub.edu.pk/index.php/JCIS/article/view/4146

Availability: https://journals.iub.edu.pk/index.php/JCIS/article/view/4146

Rekontruksi Data Suhu dan Tekanan pada Pembangkit Listrik Tenaga Mesin Gas (PLTMG) menggunakan Recurrent Neural Network

Authors: Naufaldhianto, Enggal Nur Febrian Kindhi, Berlian Al Wicaksono, Ilham Agung

Source: KARSA NUSANTARA; Vol. 2 (2025): Prosiding Seminar Nasional Karsa Nusantara 2025; 342-350 ; Kolaborasi Rekayasa dan Sains Nasional untuk Teknologi, Riset, dan Kecerdasan Buatan ; Vol 2 (2025): Prosiding Seminar Nasional Karsa Nusantara 2025; 342-350 ; 3090-1154

Subject Terms: deteksi anomali, LSTM autoencoder, peringatan dini, PLTMG

File Description: application/pdf

Relation: https://journalng.uwks.ac.id/karsanusa/article/view/537/402; https://journalng.uwks.ac.id/karsanusa/article/view/537

Availability: https://journalng.uwks.ac.id/karsanusa/article/view/537

Edge AI for Real-Time Anomaly Detection in Smart Homes

Authors: Manuel J. C. S. Reis Carlos Serôdio

Source: Future Internet ; Volume 17 ; Issue 4 ; Pages: 179

Subject Terms: edge AI, anomaly detection, smart home IoT, isolation forest, LSTM autoencoder

File Description: application/pdf

Relation: Internet of Things; https://dx.doi.org/10.3390/fi17040179

Availability: https://doi.org/10.3390/fi17040179

Text Mining and Unsupervised Deep Learning for Intrusion Detection in Smart-Grid Communication Networks

Authors: Joseph Azar Mohammed Al Saleh Raphaël Couturier et al.

Source: IoT ; Volume 6 ; Issue 2 ; Pages: 22

Subject Terms: network intrusion detection, LSTM autoencoder, Manufacturing Message Specification (MMS), smart grid security, Cyber–Physical Systems (CPSs), industrial control systems, high-dimensional time series data

File Description: application/pdf

Relation: https://dx.doi.org/10.3390/iot6020022

Availability: https://doi.org/10.3390/iot6020022

LSTM-Autoencoder-Based Incremental Learning for Industrial Internet of Things

Authors: Atallo Kassaw Takele Balázs Villányi

Source: IEEE Access, Vol 11, Pp 137929-137936 (2023)

Subject Terms: Industrial internet of things (IIoT), incremental learning, 9. Industry and infrastructure, LSTM-autoencoder, Electrical engineering. Electronics. Nuclear engineering, weight sparsification, TK1-9971

Access URL: https://doaj.org/article/04ced91100a6435c88ea62e12bed561e

Explainable predictive maintenance: autoencoders and rule-based explainer

Authors: Queiroz , Ricardo Jorge Martins

Source: Queiroz, R. J. M. (2023). Explainable predictive maintenance: autoencoders and rule-based explainer [Dissertação de Mestrado em Ciência de Dados, Universidade Portucalense]. Repositório Institucional UPT. http://hdl.handle.net/11328/5227

Subject Terms: LSTM-Autoencoder, SHAP, AMRules, Predictive maintenance, XAI, Anomaly detection, Ciências Naturais - Ciências da Computação e da Informação

File Description: application/pdf

Availability: https://hdl.handle.net/11328/5227

Data-Driven Detection of Stealth Cyber-Attacks in DC Microgrids

Authors: Abdulrahman Takiddin Suman Rath Muhammad Ismail et al.

Source: Takiddin, A, Rath, S, Ismail, M & Sahoo, S 2022, 'Data-driven Detection of Stealth Cyber-attacks in DC Microgrids', I E E E Systems Journal, vol. 16, no. 4, pp. 6097-6106. https://doi.org/10.1109/JSYST.2022.3183140

Subject Terms: Artificial intelligence, Distributed databases, Cybersecurity, cybersecurity, Detectors, Anomaly detection, 02 engineering and technology, Encoder, Machine Learning, name=SDG 7 - Affordable and Clean Energy, dc microgrids, Power electronics control, Voltage control, 0202 electrical engineering, electronic engineering, information engineering, Training, Feature extraction, Microgrids, Power Electronics, LSTM, DC microgrids, long short-term memory (LSTM)-autoencoder, name=SDG 11 - Sustainable Cities and Communities

File Description: application/pdf

Access URL: https://vbn.aau.dk/da/publications/cf6a6458-d32c-46b6-8b16-98871483f2c8
http://www.scopus.com/inward/record.url?scp=85134267107&partnerID=8YFLogxK
https://vbn.aau.dk/ws/files/472764938/FINAL_VERSION_SJ.pdf
https://doi.org/10.1109/JSYST.2022.3183140

A deep learning approach for error detection and quantification in extrusion-based bioprinting

Authors: Bonatti A. F. Vozzi G. Kai Chua C. et al.

Source: Materials Today : Proceedings

Subject Terms: 0301 basic medicine, 0303 health sciences, 03 medical and health sciences, Extrusion-based bioprinting, Quality control, Convolutional LSTM autoencoder, Deep learning