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

Monitoring autocorrelated processes using the latent vector in LSTM autoencoder

Authors: Seohyeon Jeong Dalmin Jeong Seungmin Lee et al.

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

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

Authors: Xi Chen Yu Fan Xin Lin et al.

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

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

Authors: Mai Abdelsamie Hosam Refaat Mohammed Abdallah et al.

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

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

Authors: Sara Iseed Mohammad M N Hamarsheh

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

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

Authors: Anak Agung Gde Pradnyana Aditya Firman Ihsan null Hasmawati

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

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

Authors: Jian Yang Lili Liu

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

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

Authors: Sangil Lee Hanseob Lee Dong-Gil Na et al.

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

Anomaly Behavior Detection in Mobile Robot Navigation for Repetitive Tasks Using CNN-LSTM Autoencoder Reconstruction

Authors: Sheng-Wei Sim Noriyuki Kawarazaki Danny Wee-Kiat Ng et al.

Source: 2025 IEEE International Conference on Automatic Control and Intelligent Systems (I2CACIS). :55-60

Towards Efficient Predictive Maintenance: Evaluating LSTM Autoencoders, CNNs, and RNNs for Industrial Machinery Anomaly Detection

Authors: Md. Ismail Hossian Hasanur Zaman Anonto Sudipto Roy et al.

Source: 2025 IEEE Energy Conversion Congress & Exposition Asia (ECCE-Asia). :1-6

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

Authors: null Konne Madhavi

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

Deep Learning for Anomaly Detection: A CNN-LSTM Autoencoder Approach

Authors: Vandana Pathak Manoj Diwakar Sanjay Roka et al.

Source: 2025 3rd International Conference on Advancement in Computation & Computer Technologies (InCACCT). :827-832

Fault Detection in Hydraulic Components of Wind Turbines Using SCADA Data and LSTM Autoencoders

Authors: Paulo Henrique de Lima

Subject Terms: Economia e gestão, Economics and Business

File Description: application/pdf

Availability: https://hdl.handle.net/10216/163056

Обнаружение аномалий на основе LSTM-Автокодировщик для транзакций по кредитным картам: LSTM-Autoencoder based anomaly detection for credit card transactions

Source: Scientific works of KubSTU. :62-73

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

Authors: Quakernack, Lars Engelmann, Thomas Haubrock, Jens et al.

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

Subject Terms: electrical vehicle, Autoencoder, LSTM, smart grid, control

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

Design of an improved model using federated learning and LSTM autoencoders for secure and transparent blockchain network transactions

Authors: R. Vijay Anand G. Magesh I. Alagiri et al.

Source: Sci Rep
Scientific Reports, Vol 15, Iss 1, Pp 1-18 (2025)

Subject Terms: Blockchain, Science, Machine learning, Federated learning, LSTM autoencoders, Medicine, Article, Privacy preserving

Access URL: https://doaj.org/article/02494a17aee54a549ae0e989c23c732f

Forecasting gold price using hybrid deep neural network LSTM-autoencoder

Authors: Agampreet Saini Rahul Kumar Singh Puneet Sinha

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

Subject Terms: 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

File Description: electronic resource

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

Access URL: https://doaj.org/article/8664dff01c3d468cb12b3b530daf8eb2

Abstractive text summarization from Amazon food review dataset using modified attention based Bi-LSTM autoencoder model

Authors: P L. Prabha M. Parvathy

Source: Journal of the Chinese Institute of Engineers. 48:268-282

Integrating LSTM Autoencoders in Medical Monitoring Systems for Early Diabetes Detection

Authors: Vaishnavi Dali. A David Samuel Azariya. S null Sundaram.P et al.

Source: 2025 5th International Conference on Expert Clouds and Applications (ICOECA). :1023-1029

Intrusion Detection for Edge-IoT Using LSTM-Autoencoder

Authors: Bodjré Aka Hugues Félix Kié Eba Victoire N’guessan N’takpé Christian Placide et al.

Source: Open Journal of Applied Sciences. 15:2638-2647