Search Results - Memory-based additional autoencoder*

Advanced memory forensics for malware classification with deep learning algorithms.

Authors: Odeh, Ammar Taleb, Anas Abu Alhajahjeh, Tareq et al.

Source: Cluster Computing; Oct2025, Vol. 28 Issue 6, p1-15, 15p

Subject Terms: MACHINE learning, ARTIFICIAL intelligence, RECURRENT neural networks, CONVOLUTIONAL neural networks, DATA mining, DEEP learning

Surrogate Modeling of Hydrogen-Enriched Combustion Using Autoencoder-Based Dimensionality Reduction.

Authors: Zhang, Lanfei Chu, Xu Ding, Siyu et al.

Source: Processes; Apr2025, Vol. 13 Issue 4, p1093, 21p

Subject Terms: AUTOENCODERS, JET nozzles, ENGINEERING design, FLUID flow, SPATIAL resolution, DEEP learning

Anomaly detection in urban lighting systems using autoencoder and transformer algorithms.

Authors: Śmiałkowski, Tomasz Czyżewski, Andrzej

Source: Scientific Reports; 10/15/2025, Vol. 15 Issue 1, p1-13, 13p

Subject Terms: AUTOENCODERS, MACHINE learning, ENERGY consumption, OUTLIER detection, MUNICIPAL lighting, ARTIFICIAL intelligence, TRANSFORMER models, REAL-time computing

AW-CES: adaptively weighted-cumulative error scoring for autoencoder-based anomaly detection on unlabeled data.

Authors: Park, Cheolsoon Song, Seunghwan Baek, Jun-Geol

Source: International Journal of Data Science & Analytics; Oct2025, Vol. 20 Issue 5, p4591-4610, 20p

Long Short-Term Memory-Based Fall Detection by Frequency-Modulated Continuous Wave Millimeter-Wave Radar Sensor for Seniors Living Alone.

Authors: Yu, Yun Seop Wie, Seongjo Lee, Hojin et al.

Source: Applied Sciences (2076-3417); Aug2025, Vol. 15 Issue 15, p8381, 16p

Subject Terms: LONG short-term memory, OLDER people, MACHINE learning, HUMAN activity recognition, CONTINUOUS wave radar, FEATURE extraction

Naval AI-Based Utility for Remaining Useful Life Prediction and Anomaly Detection for Lifecycle Management.

Authors: Pardo B., Carlos E. Iglesias R., Oscar I. León A., Maicol D. et al.

Source: Systems; Oct2025, Vol. 13 Issue 10, p845, 38p

Subject Terms: REMAINING useful life, LONG short-term memory, CONDITION-based maintenance, PRODUCT life cycle assessment, OUTLIER detection

Long-Short-Term-Memory-Based Deep Stacked Sequence-to-Sequence Autoencoder for Health Prediction of Industrial Workers in Closed Environments Based on Wearable Devices.

Authors: Xu, Weidong He, Jingke Li, Weihua et al.

Source: Sensors (14248220); Sep2023, Vol. 23 Issue 18, p7874, 17p

Subject Terms: INDUSTRIAL workers, WEARABLE technology, DATA acquisition systems, SPACE industrialization, SUPPORT vector machines, DEEP learning, MACHINE learning

Smart Tool Wear Monitoring of CFRP/CFRP Stack Drilling Using Autoencoders and Memory-Based Neural Networks.

Authors: Caggiano, Alessandra Mattera, Giulio Nele, Luigi

Source: Applied Sciences (2076-3417); Mar2023, Vol. 13 Issue 5, p3307, 16p

Subject Terms: CARBON fiber-reinforced plastics, RECURRENT neural networks, ARTIFICIAL intelligence, SIGNAL processing, FEEDFORWARD neural networks, FEATURE extraction, CARBON fibers

Advancing Particle Tracking: Self-Organizing Map Hyperparameter Study and Long Short-Term Memory-Based Outlier Detection.

Authors: Klein, Max Dormagen, Niklas Wimmer, Lukas et al.

Source: Machine Learning & Knowledge Extraction; Jun2025, Vol. 7 Issue 2, p37-N.PAG, 22p

Subject Terms: PARTICLE tracking velocimetry, SELF-organizing maps, FLUID dynamics, OUTLIER detection, LONG short-term memory, OPTIMIZATION algorithms, MACHINE learning

Intelligent Detection of Railway Axles Fatigue Crack Using Acoustic Emission-Stacked Denoising Autoencoders.

Authors: Lin, Li Zhao, Shuang Tang, Xiaowen et al.

Source: Journal of Nondestructive Evaluation; Dec2025, Vol. 44 Issue 4, p1-22, 22p

Subject Terms: FATIGUE cracks, ACOUSTIC emission, DEEP learning, NONDESTRUCTIVE testing, DETECTION algorithms, FEATURE extraction, AXLES

A Deep Learning-Based Method for Mechanical Equipment Unknown Fault Detection in the Industrial Internet of Things.

Authors: Liu, Xiaokai Meng, Xiangheng Ning, Lina et al.

Source: Sensors (14248220); Oct2025, Vol. 25 Issue 19, p5984, 26p

Subject Terms: DEEP learning, FAULT diagnosis, INDUSTRY 4.0, CONVOLUTIONAL neural networks, AUTOENCODERS, LONG short-term memory, OUTLIER detection, MACHINE learning

Hybrid Deep Learning Framework for Anomaly Detection in Power Plant Systems.

Authors: Wang, Shuchong Zhao, Changxiang Liu, Xingchen et al.

Source: Algorithms; Nov2025, Vol. 18 Issue 11, p704, 18p

Subject Terms: AUTOENCODERS, TRANSFORMER models, ENSEMBLE learning, OUTLIER detection, ELECTRIC power plants, GAUSSIAN mixture models

A novel methodology based on long short-term memory stacked autoencoders for unsupervised detection of abnormal working conditions in semiconductor manufacturing systems.

Authors: Hosseinpour, Fatemeh Ahmed, Ibrahim Baraldi, Piero et al.

Source: Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk & Reliability; Oct2025, Vol. 239 Issue 5, p1115-1133, 19p

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

Authors: Rehouma, Haythem Boukadoum, Mounir

Source: Sensors (14248220); Oct2025, Vol. 25 Issue 19, p6035, 16p

Subject Terms: DEEP learning, MULTISENSOR data fusion, ONLINE monitoring systems, ELDER care, MOTION detectors, ACCIDENTAL fall prevention, POSTURE

Mori–Zwanzig latent space Koopman closure for nonlinear autoencoder.

Authors: Gupta, Priyam Schmid, Peter Sipp, Denis et al.

Source: Proceedings of the Royal Society A: Mathematical, Physical & Engineering Sciences; 5/1/2025, Vol. 481 Issue 2313, p1-28, 28p

Subject Terms: AUTOENCODERS, NONLINEAR systems

A Comparative Study of Dimensionality Reduction Methods for Accurate and Efficient Inverter Fault Detection in Grid-Connected Solar Photovoltaic Systems.

Authors: Tufail, Shahid Sarwat, Arif I.

Source: Electronics (2079-9292); Jul2025, Vol. 14 Issue 14, p2916, 19p

Subject Terms: PRINCIPAL components analysis, MACHINE learning, AUTOENCODERS, RANDOM forest algorithms, K-nearest neighbor classification, DIMENSIONAL reduction algorithms, PHOTOVOLTAIC power systems, FAULT diagnosis

Achieving State-of-the-art Accuracy in Arabic Sign Language Recognition with VideoMAE and Data Augmentation.

Authors: Alkahtani, Bader Nasser Alsraisri, Naseem Almalki, Ali Jaber

Source: Journal of Disability Research; Oct2025, Vol. 4 Issue 5, p1-11, 11p

Subject Terms: DATA augmentation, TRANSFORMER models, ARABIC language, HUMAN activity recognition, REAL-time computing, MEANS of communication for deaf people, MACHINE learning

An Optimized Transformer–GAN–AE for Intrusion Detection in Edge and IIoT Systems: Experimental Insights from WUSTL-IIoT-2021, EdgeIIoTset, and TON_IoT Datasets.

Authors: Salehiyan, Ahmad Moghaddam, Pardis Sadatian Kaveh, Masoud

Source: Future Internet; Jul2025, Vol. 17 Issue 7, p279, 34p

Subject Terms: INTRUSION detection systems (Computer security), EDGE computing, AUTOENCODERS, INTERNET security, CYBER physical systems, DEEP learning, GENERATIVE adversarial networks

A Secure, Blockchain-Enabled Vehicular Sensor Communication Protocol With Deep Learning-Assisted Anomaly Detection.

Authors: Mishra, Sumit Sengar, Neha Har, Dongsoo

Source: IEEE Intelligent Transportation Systems Magazine; May/Jun2025, Vol. 17 Issue 3, p88-95, 8p

Hybrid Memory-Enhanced Autoencoder with Adversarial Training for Anomaly Detection in Virtual Power Plants.

Authors: Liu, Yuqiao Pan, Chen Oh, YeonJae et al.

Source: Computers, Materials & Continua; 2025, Vol. 82 Issue 3, p4593-4629, 37p

Subject Terms: AUTOENCODERS, SOLAR radiation, POWER plants, INTEGRALS, MEMORY