Výsledky vyhledávání - Quantified Autoencoder

Quantified active learning Kriging-based Bayesian updating for high-dimensional models using convolutional autoencoders

Autoři: I. Prentzas M. Fragiadakis

Zdroj: 16th World Congress on Computational Mechanics and 4th Pan American Congress on Computational Mechanics.

From Envelope Spectra to Bearing Remaining Useful Life: An Intelligent Vibration-Based Prediction Model with Quantified Uncertainty

Autoři: Haobin Wen Long Zhang Jyoti K. Sinha

Zdroj: Sensors, Vol 24, Iss 22, p 7257 (2024)

Témata: bearings, remaining useful life, vibration, prognostics and health management, variational autoencoder, uncertainty quantification, Chemical technology, TP1-1185

Popis souboru: electronic resource

Relation: https://www.mdpi.com/1424-8220/24/22/7257; https://doaj.org/toc/1424-8220

Přístupová URL adresa: https://doaj.org/article/33c0bdc385be422384a0bdaaa9c37a4c

Anomaly Detection and Objective Security Evaluation Using Autoencoder, Isolation Forest, and Multi-Criteria Decision Methods.

Autoři: Zhang, Hongbin Zhang, Haibin

Zdroj: Sensors (14248220). Oct2025, Vol. 25 Issue 19, p6250. 16p.

Témata: *ANOMALY detection (Computer security), *AUTOENCODERS, *MULTIPLE criteria decision making, *RISK assessment, *INTERNET security, *DIMENSIONAL reduction algorithms, *PREDICTION models, *OUTLIER detection

Short-Term Natural Gas Load Forecasting Based on GSTAE-Dropout Autoencoder.

Autoři: WANG Zeyu GUO Junming I. I. Baolong a další

Zdroj: Journal of Beijing Institute of Petrochemical Technology. Jun2025, Vol. 33 Issue 2, p49-56. 8p.

Témata: *AUTOENCODERS, *NATURAL gas, *FORECASTING, *FEATURE extraction, *F-test (Mathematical statistics), *PREDICTION models

Machine-learning approach for quantified resolvability enhancement of low-dose STEM data

Autoři: Laura Gambini Tiarnan Mullarkey Lewys Jones a další

Zdroj: Machine Learning: Science and Technology, Vol 4, Iss 1, p 015025 (2023)

Témata: scanning transmission electron microscope, image denoising, Poisson noise, autoencoder, Computer engineering. Computer hardware, TK7885-7895, Electronic computers. Computer science, QA75.5-76.95

Popis souboru: electronic resource

Relation: https://doaj.org/toc/2632-2153

Přístupová URL adresa: https://doaj.org/article/95f7cc3c3cc74d5aa282dbee1db97996

Robust Damage Detection and Localization Under Varying Environmental Conditions Using Neural Networks and Input‐Residual Correlations.

Autoři: Römgens, Niklas Abbassi, Abderrahim Fürll, Florian a další

Zdroj: Structural Control & Health Monitoring; 5/23/2025, Vol. 2025, p1-20, 20p

Témata: STRUCTURAL health monitoring, AUTOENCODERS, PEARSON correlation (Statistics), STRUCTURAL models, TIME series analysis

Intelligent Fault Detection Scheme for Rolling Bearing Based on Generative Adversarial Network and AutoEncoders Using Convolutional Neural Network.

Autoři: Rathore, Maan Singh Harsha, S. P.

Zdroj: Journal of Vibration Engineering & Technologies; Dec2024, Vol. 12 Issue 8, p8979-8991, 13p

Témata: CONVOLUTIONAL neural networks, GENERATIVE adversarial networks, DATA augmentation, ARTIFICIAL intelligence, AUTOENCODERS, DEEP learning, MONITORING of machinery, ROLLER bearings

A Hybrid Artificial Intelligence for Fault Detection and Diagnosis of Photovoltaic Systems Using Autoencoders and Random Forests Classifiers.

Autoři: Ratsheola, Katlego Setlhaolo, Ditiro Rasool, Akhtar a další

Zdroj: Eng (2673-4117); Oct2025, Vol. 6 Issue 10, p254, 17p

Témata: PHOTOVOLTAIC power systems, AUTOENCODERS, ARTIFICIAL intelligence, DIAGNOSIS, FAULT diagnosis, RANDOM forest algorithms, OUTLIER detection, LONG short-term memory

A Deep Autoencoder Compression-Based Genomic Prediction Method for Whole-Genome Sequencing Data.

Autoři: Song, Hailiang Dong, Tian Wang, Wei a další

Zdroj: Biology (2079-7737); Nov2025, Vol. 14 Issue 11, p1622, 17p

Témata: WHOLE genome sequencing, AUTOENCODERS, ANIMAL breeding, OPTIMIZATION algorithms, DATA compression, DATA structures, ARTIFICIAL intelligence

MASE-GC: a multi-omics autoencoder and stacking ensemble framework for gastric cancer classification.

Autoři: Liu, Di Che, Zhongguang Xu, Guannan a další

Zdroj: Frontiers in Cell & Developmental Biology; 2025, p1-14, 14p

Témata: STOMACH cancer, MULTIOMICS, DATA integration, AUTOENCODERS, CLASSIFICATION, ENSEMBLE learning, INDIVIDUALIZED medicine, BIOINFORMATICS

Ranking-enhanced anomaly detection using Active Learning-assisted Attention Adversarial Dual AutoEncoder.

Autoři: Benabderrahmane, Sidahmed Cheney, James Rahwan, Talal

Zdroj: Scientific Reports; 11/24/2025, Vol. 15 Issue 1, p1-42, 42p

Témata: ANOMALY detection (Computer security), ACTIVE learning, AUTOENCODERS, INFORMATION asymmetry, INTERNET security

Integrated Machine Learning Using Autoencoder and Multilayer Perceptron Approaches to Predict Stress–Strain Curves of Frozen Soil–Rock Mixtures.

Autoři: Sun, Kai Li, Zhiqing Wang, Haosen a další

Zdroj: International Journal of Geomechanics; Oct2025, Vol. 25 Issue 10, p1-15, 15p

Témata: STRESS-strain curves, MACHINE learning, AUTOENCODERS, GEOTECHNICAL engineering, MULTILAYER perceptrons, FEATURE extraction

Denoising Autoencoder for Reconstructing Sensor Observation Data and Predicting Evapotranspiration: Noisy and Missing Values Repair and Uncertainty Quantification.

Autoři: Johnsen, Timothy K. Bi, Xiangyu Chou, Chunwei a další

Zdroj: Water Resources Research; Oct2025, Vol. 61 Issue 10, p1-23, 23p

Témata: EVAPOTRANSPIRATION, AUTOENCODERS, STOCHASTIC analysis, MACHINE learning, HYDROLOGICAL forecasting, NOISE control, TELEMETRY

Spatial-Frequency-Scale Variational Autoencoder for Enhanced Flow Diagnostics of Schlieren Data.

Autoři: Yang, Ronghua Wu, Hao Yang, Rongfei a další

Zdroj: Sensors (14248220); Oct2025, Vol. 25 Issue 19, p6233, 29p

Témata: FLUID dynamics, AUTOENCODERS, FLOW visualization, FOURIER transforms, DEEP learning, FEATURE extraction, FORECASTING

Comparative Analysis of Binarization Approaches for Automated Dye Penetrant Testing.

Autoři: Haupts, Peter Josef Al-Joumaa, Hammoud Al-Shrouf, Loui a další

Zdroj: Processes; Apr2025, Vol. 13 Issue 4, p1212, 28p

Témata: MANUFACTURING processes, QUALITY control, STEEL pipe, NONDESTRUCTIVE testing, AUTOENCODERS

An autoencoder and vision transformer based interpretability analysis on the performance differences in automated staging of second and third molars.

Autoři: Buyukcakir, Barkin De Tobel, Jannick Thevissen, Patrick a další

Zdroj: Scientific Reports; 11/26/2025, Vol. 15 Issue 1, p1-19, 19p

Témata: AUTOENCODERS, TRANSFORMER models, DIAGNOSIS, FORENSIC engineering, HETEROGENEITY, DENTAL maturity

Unsupervised Convolutional Transformer Autoencoder for Robust Health Indicator Construction and RUL Prediction in Rotating Machinery.

Autoři: Dahal, Amrit Huang, Hong-Zhong Huang, Cheng-Geng a další

Zdroj: Applied Sciences (2076-3417); Oct2025, Vol. 15 Issue 20, p10972, 22p

Témata: REMAINING useful life, CONVOLUTIONAL neural networks, VIBRATION measurements, MACHINE learning, ENGINEERING systems, TRANSFORMER models, AUTOENCODERS

A Fault Diagnosis Method for the Train Communication Network Based on Active Learning and Stacked Consistent Autoencoder.

Autoři: Yang, Yueyi Wang, Haiquan Nie, Xiaobo a další

Zdroj: Symmetry (20738994); Oct2025, Vol. 17 Issue 10, p1622, 17p

Témata: FAULT diagnosis, ACTIVE learning, AUTOENCODERS, PATTERN recognition systems, METADATA, RELIABILITY in engineering, RAILROAD communication systems, MACHINE learning

Enhancing SNR in CEST imaging: A deep learning approach with a denoising convolutional autoencoder.

Autoři: Kurmi, Yashwant Viswanathan, Malvika Zu, Zhongliang

Zdroj: Magnetic Resonance in Medicine; Dec2024, Vol. 92 Issue 6, p2404-2419, 16p

Témata: OVERHAUSER effect (Nuclear physics), MAGNETIZATION transfer, DEEP learning, IMAGE denoising, PROTONS

Wind Turbine Fault Detection Through Autoencoder-Based Neural Network and FMSA.

Autoři: Nogueira, Welker Facchini Melani, Arthur Henrique de Andrade de Souza, Gilberto Francisco Martha

Zdroj: Sensors (14248220); Jul2025, Vol. 25 Issue 14, p4499, 41p

Témata: WIND turbines, AUTOENCODERS, OUTLIER detection, CONDITION-based maintenance, FAILURE analysis, CLEAN energy, ARTIFICIAL neural networks, FAULT diagnosis