Výsledky vyhledávání - LSTM autoencoder*

Detecting Zero-Day Web Attacks with an Ensemble of LSTM, GRU, and Stacked Autoencoders

Autoři: Babaey, Vahid Faragardi, Hamid Reza

Zdroj: Computers. 14(6)

Témata: autoencoder, ensemble classification, GRU, LSTM, neural networks, stacked, tokenization, zero-day attacks

Popis souboru: print

Přístupová URL adresa: https://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-368654
https://doi.org/10.3390/computers14060205

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

Autoři: Maulana Ahsan Fadillah Yenni Angraini Rahma Anisa

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

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

Přístupová URL adresa: https://doaj.org/article/40bb9600e82a47f0a6decd94607ceb8a

Intelligent Autoencoder with LSTM based Intrusion Detection and Recommender System

Autoři: V. G. Aishvarya Shree M. Thangaraj

Zdroj: International Journal of Computer Network and Information Security. 17:45-62

Non-Line-of-Sight Multipath Classification Method for BDS Using Convolutional Sparse Autoencoder with LSTM

Autoři: Qin, Yahang Li, Zhenni Xie, Shengli a další

Zdroj: Tsinghua Science and Technology. 30:68-86

Témata: Satellites, Multipath classification, BeiDou Navigation Satellite System (BDS), Solid modeling, Three-dimensional displays, Long short-term memory (LSTM), Convolutional sparse autoencoder, Interference, Urban areas, Convolution, Long short term memory

LSTM Autoencoder Model to Identify Electric Vehicles in Grouped Smart Meter Data

Autoři: Quakernack, Lars Engelmann, Thomas Haubrock, Jens a další

Zdroj: 2024 IEEE PES Innovative Smart Grid Technologies Europe (ISGT EUROPE). :1-5

Témata: electrical vehicle, Autoencoder, LSTM, smart grid, control

Přístupová URL adresa: https://pub.uni-bielefeld.de/record/3004508
https://doi.org/10.1109/isgteurope62998.2024.10863725

Forecasting gold price using hybrid deep neural network LSTM-autoencoder

Autoři: Agampreet Saini Rahul Kumar Singh Puneet Sinha

Zdroj: Discover Artificial Intelligence, Vol 5, Iss 1, Pp 1-19 (2025)

Témata: Gold price prediction, LSTM, CNN, Autoencoders, Hybrid models, Time series forecasting, Computational linguistics. Natural language processing, P98-98.5, Electronic computers. Computer science, QA75.5-76.95

Popis souboru: electronic resource

Relation: https://doaj.org/toc/2731-0809

Přístupová URL adresa: https://doaj.org/article/8664dff01c3d468cb12b3b530daf8eb2

Anomaly Detection of Gas Pipeline Operational Data Using TCN-Autoencoder and LSTM-Autoencoder Models

Autoři: Anak Agung Gde Pradnyana Aditya Firman Ihsan null Hasmawati

Zdroj: 2025 International Conference on Data Science and Its Applications (ICoDSA). :1347-1352

Hybrid Outlier Detection Framework Based on Optimized KMeans and HDBSCAN Using Bat Algorithm and LSTM Autoencoder

Autoři: Mai Abdelsamie Hosam Refaat Mohammed Abdallah a další

Zdroj: Statistics, Optimization & Information Computing. 14:970-1017

Monitoring autocorrelated processes using the latent vector in LSTM autoencoder

Autoři: Seohyeon Jeong Dalmin Jeong Seungmin Lee a další

Zdroj: Korean Journal of Applied Statistics. 38:439-454

Adversarial Data Augmentation Enhanced LSTM Autoencoder for Anomaly Detection in Industrial Pipeline Networks

Autoři: Xi Chen Yu Fan Xin Lin a další

Zdroj: Journal of Signal Processing Systems. 97:197-207

An Ensemble Deep Learning Model Using CNN, LSTM and Autoencoder for EEG-Based Parkinson’s Disease Classification

Autoři: Mallarapu Vijay Kumar Ramamohana Rao Gudaru Jagabathula Sai Sandeep a další

Zdroj: 2025 International Conference on Innovations in Intelligent Systems: Advancements in Computing, Communication, and Cybersecurity (ISAC3). :1-6

Video Anomaly Detection Based on 3D-CNN Autoencoder with Bidirectional LSTM

Autoři: Mohan Sankaran Nagaraju Jooluri Balasundaram Subbusundaram a další

Zdroj: 2025 3rd International Conference on Data Science and Network Security (ICDSNS). :1-5

Performance Evaluation of LSTM Autoencoder for Behavioral-Based Insider Threat Detection

Autoři: Sara Iseed Mohammad M N Hamarsheh

Zdroj: 2025 International Conference on Smart Applications, Communications and Networking (SmartNets). :1-6

Lateral walking gait phase recognition for hip exoskeleton by denoising autoencoder-LSTM

Autoři: Mingxiang Luo Xiaoli Dong Hongliu Yu a další

Zdroj: Comput Struct Biotechnol J
Computational and Structural Biotechnology Journal, Vol 28, Iss, Pp 50-62 (2025)

Témata: Hip exoskeleton, DAE-LSTM, Lateral walking gait recognition, TP248.13-248.65, IMUs, Biotechnology, Research Article

Přístupová URL adresa: https://pubmed.ncbi.nlm.nih.gov/40026802
https://doaj.org/article/5a80ff576a0b4d0fa61a5f8a8de82534

Anomaly Prediction Based On LSTM And Autoencoders Using Federated Learning In Financial Transactions- Survey

Autoři: Gaurav Kumar Dr. Pushpendra Kumar Verma

Zdroj: International Journal of Environmental Sciences. :238-249

Robust Anomaly Detection in Financial Markets Using LSTM Autoencoders and Generative Adversarial Networks

Autoři: Jian Yang Lili Liu

Zdroj: Engineering: Open Access. 3:01-11

A Hybrid LSTM-Autoencoder Framework for Accurate Prediction of Diabetic Kidney Disease

Autoři: null Konne Madhavi

Zdroj: Journal of Information Systems Engineering and Management. 10:929-941

Convolutional LSTM Neural Network Autoencoder Based Fault Detection in Manufacturing Predictive Maintenance

Autoři: Young Jun Park

Zdroj: Journal of Machine and Computing. :914-923

LSTM-Based Stacked Autoencoders for Early Anomaly Detection in Induction Heating Systems

Autoři: Qais, Mohammed H. Kewat, Seema Loo, Ka Hong a další

Zdroj: Mathematics. 11(15)

Témata: anomaly detection, autoencoder, deep learning, induction heating system, LSTM, Electrical Engineering, Elektroteknik

Popis souboru: electronic

Přístupová URL adresa: https://urn.kb.se/resolve?urn=urn:nbn:se:kau:diva-96455
https://doi.org/10.3390/math11153319

Development and Model Compression of CNN-LSTM-Autoencoder Model for Anomaly Detection of UAVs

Autoři: Sangil Lee Hanseob Lee Dong-Gil Na a další

Zdroj: Journal of Society of Korea Industrial and Systems Engineering. 48:155-162