Výsledky vyhledávání - stacked denoised autoencoder

Fault detection and recognition of multivariate process based on feature learning of one-dimensional convolutional neural network and stacked denoised autoencoder

Autoři: Jianbo Yu Shijin Wang Chengyi Zhang

Zdroj: International Journal of Production Research. 59:2426-2449

Témata: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Přístupová URL adresa: https://www.tandfonline.com/doi/full/10.1080/00207543.2020.1733701
https://ideas.repec.org/a/taf/tprsxx/v59y2021i8p2426-2449.html

Coupled fault diagnosis for centrifugal pumps through Boruta-Shap feature selection and rime-enhanced stacked denoised autoencoder.

Autoři: Hu, Kang Sun, Hui Fan, Wei a další

Zdroj: Engineering Applications of Artificial Intelligence. Dec2025:Part D, Vol. 162, pN.PAG-N.PAG. 1p.

Témata: *FAULT diagnosis, *CENTRIFUGAL pumps, *CAVITATION, *CONDITION-based maintenance, *IMPELLERS, *FEATURE selection, *AUTOENCODERS

Extract Features Using Stacked Denoised Autoencoder

Autoři: Lin Zhu Yong Gan Yushu Gao a další

Zdroj: Lecture Notes in Computer Science ISBN: 9783319093291

Přístupová URL adresa: https://link.springer.com/chapter/10.1007/978-3-319-09330-7_2
https://link.springer.com/10.1007/978-3-319-09330-7_2
https://rd.springer.com/chapter/10.1007/978-3-319-09330-7_2
https://dblp.uni-trier.de/db/conf/icic/icic2014-3.html#GaoZZGS14

A denoising method for ECG signals based on CEEMDAN-TSO and stacked sparse autoencoders

Autoři: Shun Li Juan Li Jiandong Mao a další

Zdroj: Computers in Biology and Medicine. 188:109818

Přístupová URL adresa: https://pubmed.ncbi.nlm.nih.gov/39983358

Fault detection and recognition of multivariate process based on feature learning of one-dimensional convolutional neural network and stacked denoised autoencoder.

Autoři: Zhang, Chengyi Yu, Jianbo Wang, Shijin

Zdroj: International Journal of Production Research; Apr2021, Vol. 59 Issue 8, p2426-2449, 24p, 2 Color Photographs, 3 Diagrams, 15 Charts, 4 Graphs

Témata: CONVOLUTIONAL neural networks, SIGNAL convolution, FAULT diagnosis, ARTIFICIAL neural networks, MANUFACTURING processes, SIGNAL processing, DEEP learning, CONVEYOR belts

Denoising magnetic resonance spectroscopy (MRS) data using stacked autoencoder for improving signal‐to‐noise ratio and speed of MRS

Autoři: Wang, Jing Ji, Bing Lei, Yang a další

Zdroj: Medical Physics. 50:7955-7966

Témata: Magnetic Resonance Spectroscopy, Image Processing, Computer-Assisted, Humans, Brain, FOS: Physical sciences, Medical Physics (physics.med-ph), Signal-To-Noise Ratio, Physics - Medical Physics, Magnetic Resonance Imaging

Přístupová URL adresa: https://pubmed.ncbi.nlm.nih.gov/37947479
https://pubmed.ncbi.nlm.nih.gov/37033456
http://arxiv.org/abs/2303.16503

Automated Atrial Fibrillation Classification Based on Denoising Stacked Autoencoder and Optimized Deep Network

Autoři: Singh, Prateek Sharma, Ambalika Maiya, Shreesha

Témata: Electrical Engineering and Systems Science - Signal Processing, Computer Science - Machine Learning, Electrical Engineering and Systems Science - Image and Video Processing, text

URL: http://arxiv.org/abs/2202.05177

Fault Diagnosis for Hydraulic Servo System: A Stacked Denoising Autoencoder Method based on Self-Learning of Robustness Features

Autoři: Zhenya Wang Hu Huang Han Te a další

Zdroj: 2020 Chinese Automation Congress (CAC). :4479-4483

Témata: 8. Economic growth, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Přístupová URL adresa: http://xplorestaging.ieee.org/ielx7/9326315/9326464/09326938.pdf?arnumber=9326938
http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=9326938

A Deep Learning Framework for Univariate Time Series Prediction Using Convolutional LSTM Stacked Autoencoders

Autoři: Cinzia Giannetti Aniekan Essien

Zdroj: 2019 IEEE International Symposium on INnovations in Intelligent SysTems and Applications (INISTA). :1-6

Témata: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Přístupová URL adresa: https://cronfa.swan.ac.uk/Record/cronfa51622/Download/0051622-29082019102938.pdf
https://cronfa.swan.ac.uk/Record/cronfa51622/Download/0051622-29082019102938.pdf
https://ieeexplore.ieee.org/document/8778417/
https://cronfa.swansea.ac.uk/Record/cronfa51622/Details
https://cronfa.swansea.ac.uk/Record/cronfa51622/Download/0051622-29082019102938.pdf
https://dblp.uni-trier.de/db/conf/inista/inista2019.html#EssienG19
https://doi.org/10.1109/INISTA.2019.8778417

Fault Diagnosis of High-Voltage Circuit Breakers Using Hilbert-Huang Transform and Denoising-Stacked Autoencoder

Autoři: Song Dongbo Cai Mengyi Jing Yan a další

Zdroj: 2019 4th International Conference on Power and Renewable Energy (ICPRE). :228-232

Témata: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Přístupová URL adresa: http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=9034783
http://xplorestaging.ieee.org/ielx7/9028046/9034534/09034783.pdf?arnumber=9034783

Temporal denoising and deep feature learning for enhanced defect detection in thermography using stacked denoising convolution autoencoder.

Autoři: Yerneni, Naga Prasanthi Ghali, V.S. Vesala, G.T. a další

Zdroj: Infrared Physics & Technology. Dec2024, Vol. 143, pN.PAG-N.PAG. 1p.

Témata: *MILD steel, *SIGNAL-to-noise ratio, *THERMOGRAPHY, *DEEP learning, *CARBON steel

Enhanced defect detection in thermography through temporal denoising and deep feature extraction using a shallow convolution autoencoder.

Autoři: Prasanthi, Y. Naga Ghali, V. S. Vesala, G. T. a další

Zdroj: Insight: Non-Destructive Testing & Condition Monitoring. Mar2025, Vol. 67 Issue 3, p162-171. 10p.

Automated atrial fibrillation classification based on denoising stacked autoencoder and optimized deep network

Autoři: Prateek Singh Ambalika Sharma Shreesha Maiya

Zdroj: Expert Systems with Applications. 233:120975

Témata: Signal Processing (eess.SP), FOS: Computer and information sciences, Computer Science - Machine Learning, 03 medical and health sciences, 0302 clinical medicine, Image and Video Processing (eess.IV), 0202 electrical engineering, electronic engineering, information engineering, FOS: Electrical engineering, electronic engineering, information engineering, 02 engineering and technology, Electrical Engineering and Systems Science - Signal Processing, Electrical Engineering and Systems Science - Image and Video Processing, Machine Learning (cs.LG)

Přístupová URL adresa: http://arxiv.org/abs/2202.05177

Stacked Denoising Autoencoder: A Learning-Based Algorithm for the Reconstruction of Handwritten Digits

Autoři: Nahid Guard Suneeta V. Budihal Huzaifa M. Maniyar

Zdroj: Advances in Intelligent Systems and Computing ISBN: 9789811563522

Přístupová URL adresa: https://dblp.uni-trier.de/db/conf/icacie/icacie2019-2.html#ManiyarGB19
https://link.springer.com/chapter/10.1007/978-981-15-6353-9_34

Denoised Bottleneck Features From Deep Autoencoders for Telephone Conversation Analysis

Autoři: Janod, Killian Morchid, Mohamed Dufour, Richard a další

Přispěvatelé: Janod, Killian Morchid, Mohamed Dufour, Richard a další

Zdroj: IEEE/ACM Transactions on Audio, Speech, and Language Processing. 25:1809-1820

Témata: [INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI], 0202 electrical engineering, electronic engineering, information engineering, [INFO.INFO-TT] Computer Science [cs]/Document and Text Processing, 02 engineering and technology

Přístupová URL adresa: https://hal.science/hal-02356138v1
https://doi.org/10.1109/taslp.2017.2718843
http://ieeexplore.ieee.org/document/7954983/
https://dblp.uni-trier.de/db/journals/taslp/taslp25.html#JanodMDLM17
https://doi.org/10.1109/TASLP.2017.2718843
https://ieeexplore.ieee.org/document/7954983/
https://hal.archives-ouvertes.fr/hal-02356138

Extract Features Using Stacked Denoised Autoencoder.

Autoři: Gao, Yushu Zhu, Lin Zhu, Hao-Dong a další

Zdroj: Intelligent Computing in Bioinformatics; 2014, p10-14, 5p

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

Dose Reduction in Scintigraphic Imaging Through Enhanced Convolutional Autoencoder-Based Denoising.

Autoři: Bouzianis, Nikolaos Stathopoulos, Ioannis Valsamaki, Pipitsa a další

Zdroj: Journal of Imaging; Jun2025, Vol. 11 Issue 6, p197, 28p

Autoencoder with Constraints for Subsurface Defect Detection in Quadratic Frequency Modulated Thermal Wave Imaging.

Autoři: Bandari, Enosh Oleti, Siva Subrahmanyam Prasanthi, Y. Naga a další

Zdroj: Sensing & Imaging; 8/18/2025, Vol. 26 Issue 1, p1-17, 17p

Financial time series forecasting using artificial neural networks

Autoři: Cardoso, Luís Gil Miguéns

Témata: Time series forecasting, Artificial neural networks, Stock market, Long short-term memory, Stacked autoencoder

Popis souboru: application/pdf

Dostupnost: http://hdl.handle.net/10071/21560