Výsledky vyhledávání - semi-supervised convolutional variational autoencoder*

Anomaly Detection Based on Graph Convolutional Network–Variational Autoencoder Model Using Time-Series Vibration and Current Data.

Autoři: Choi, Seung-Hwan An, Dawn Lee, Inho a další

Zdroj: Mathematics (2227-7390). Dec2024, Vol. 12 Issue 23, p3750. 16p.

Témata: *INDUSTRIAL robots, *ANOMALY detection (Computer security), *AUTOENCODERS, *SYSTEM failures, *FEATURE extraction, *DEEP learning

An Improved Semi-supervised Variational Autoencoder with Gate Mechanism for Text Classification.

Autoři: Ye, Haiming Zhang, Weiwen Nie, Mengna

Zdroj: International Journal of Pattern Recognition & Artificial Intelligence. Aug2022, Vol. 36 Issue 10, p1-21. 21p.

Témata: *SUPERVISED learning, *CONVOLUTIONAL neural networks, *DEEP learning

A novel semi-supervised power transformer defect monitoring technique using unreliable pseudo-labels with highly imbalanced partial discharge signals.

Autoři: Rajamayil, Manimala Basharan, Vigneshwaran

Zdroj: Electrical Engineering. Apr2025, Vol. 107 Issue 4, p4939-4957. 19p.

Témata: *LONG short-term memory, *CONVOLUTIONAL neural networks, *AUTOENCODERS, *MARGINAL distributions, *ELECTRIC transformers

Deep Residual Learning-Based Convolutional Variational Autoencoder For Driver Fatigue Classification

Autoři: Sameera Adhikari Senaka Amarakeerthi

Zdroj: Advances in Technology. :277-290

Témata: 03 medical and health sciences, 0302 clinical medicine, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Semi-supervised diagnosis method of refrigeration compressor hidden defect based on convolutional transformer autoencoder model.

Autoři: Li, Kang Sun, Zhe Jin, Huaqiang a další

Zdroj: International Journal of Refrigeration. Feb2024, Vol. 158, p47-57. 11p.

Témata: *TRANSFORMER models, *DIAGNOSIS, *COMPRESSORS, *NOISE control, *SIGNAL-to-noise ratio, *SUPERVISED learning, *MAGNETIC entropy

Deep Convolutional Variational Autoencoder for Anomalous Sound Detection

Autoři: Dai Bui Huy-Dung Han Minh-Hieu Nguyen a další

Zdroj: 2020 IEEE Eighth International Conference on Communications and Electronics (ICCE). :313-318

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

Přístupová URL adresa: http://xplorestaging.ieee.org/ielx7/9352035/9352036/09352085.pdf?arnumber=9352085
http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=9352085

A Semi-Supervised Approach For Identifying Abnormal Heart Sounds Using Variational Autoencoder

Autoři: Avik Ghose Rohan Banerjee

Zdroj: ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). :1249-1253

Témata: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology, 3. Good health

Přístupová URL adresa: https://ieeexplore.ieee.org/abstract/document/9054632
https://dblp.uni-trier.de/db/conf/icassp/icassp2020.html#BanerjeeG20

Exploring the Latent Space of Person-Specific Convolutional Autoencoders for Eye-Blink Artefact Mitigation in EEG Signals

Autoři: Criscuolo, Sabatina Giugliano, Salvatore Apicella, Andrea a další

Zdroj: 2024 IEEE 8th Forum on Research and Technologies for Society and Industry Innovation (RTSI). :414-419

Témata: Eye blink Artefacts Detection, Autoencoders, Electroencephalography, Explain-able Artificial Intelligence, Eye-blink Artefacts Detection, Latent Space interpretation, Explain able Artificial Intelligence, Electroencephalography, Autoencoders, Eye blink Artefacts Detection, Latent Space interpretation, Explain able Artificial Intelligence

Popis souboru: application/pdf

Přístupová URL adresa: https://hdl.handle.net/11588/991117

Semi-Supervised Representation Learning for Infants Biliary Atresia Screening Using Deep CNN-Based Variational Autoencoder

Autoři: Dahao Zhang Bin Wang Ling Li a další

Zdroj: Advances in Intelligent Systems and Computing ISBN: 9783030002138

Přístupová URL adresa: https://link.springer.com/chapter/10.1007/978-3-030-00214-5_148

Intrusion Detection for Blockchain‐Based Internet of Things Using Gaussian Mixture–Fully Convolutional Variational Autoencoder Model.

Autoři: Om Kumar, C. U. Marappan, Suguna Murugeshan, Bhavadharini a další

Zdroj: International Journal of Network Management; Nov/Dec2024, Vol. 34 Issue 6, p1-17, 17p

Témata: SMART cities, SMART devices, DEEP learning, INTERNET of things, DATA quality, INTRUSION detection systems (Computer security)

Exploring semi-supervised variational autoencoders for biomedical relation extraction.

Autoři: Zhang, Yijia Lu, Zhiyong

Zdroj: Methods. Aug2019, Vol. 166, p112-119. 8p.

Témata: *BIG data, *EXTRACTION (Chemistry), *EXTRACTION techniques, *SUPERVISED learning, *SHORT-term memory, *PROTEIN-protein interactions

Prognosis prediction of patients with malignant pleural mesothelioma using conditional variational autoencoder on 3D PET images and clinical data.

Autoři: Matsuo, Hidetoshi Kitajima, Kazuhiro Kono, Atsushi K. a další

Zdroj: Medical Physics. Dec2023, Vol. 50 Issue 12, p7548-7557. 10p.

Témata: *POSITRON emission tomography computed tomography, *POSITRON emission tomography, *THREE-dimensional imaging, *DIAGNOSTIC imaging, *RECEIVER operating characteristic curves, *SURVIVAL analysis (Biometry), *STOCHASTIC learning models

Unsupervised deep learning approach for structural anomaly detection using probabilistic features.

Autoři: Wan, Hua-Ping Zhu, Yi-Kai Luo, Yaozhi a další

Zdroj: Structural Health Monitoring; Jan2025, Vol. 24 Issue 1, p3-33, 31p

Témata: MACHINE learning, STRUCTURAL health monitoring, DISTRIBUTION (Probability theory), AUTOENCODERS, VECTOR data, DEEP learning

Supervised and semi-supervised deep probabilistic models for indoor positioning problems.

Autoři: Qian, Weizhu Lauri, Fabrice Gechter, Franck

Zdroj: Neurocomputing. May2021, Vol. 435, p228-238. 11p.

Témata: *SUPERVISED learning, *RECURRENT neural networks, *CONVOLUTIONAL neural networks

Multi-Dimensional Anomaly Detection and Fault Localization in Microservice Architectures: A Dual-Channel Deep Learning Approach with Causal Inference for Intelligent Sensing.

Autoři: Xing, Suchuan Wang, Yihan Liu, Wenhe

Zdroj: Sensors (14248220). Jun2025, Vol. 25 Issue 11, p3396. 32p.

Témata: *CONVOLUTIONAL neural networks, *SUPERVISED learning, *CAUSAL inference, *ROOT cause analysis, *SERVER farms (Computer network management), *DEEP learning

Unsupervised detection of high-frequency oscillations in intracranial electroencephalogram: promoting a valuable automated diagnostic tool for epilepsy.

Autoři: Chen, Wenjing Kang, Tongzhou Heyat, Md Belal Bin a další

Zdroj: Frontiers in Neurology; 2025, p1-11, 11p

Témata: K-means clustering, WAVELET transforms, AUTOENCODERS, MACHINE learning, PEOPLE with epilepsy

Unsupervised convolutional variational autoencoder deep embedding clustering for Raman spectra.

Autoři: Yixin Guo Weiqi Jin Weilin Wang a další

Zdroj: Analytical Methods; 10/21/2022, Vol. 14 Issue 39, p3898-3910, 13p

A semi-supervised temporal modeling strategy integrating VAE and Wasserstein GAN under sparse sampling constraints.

Autoři: Hu, Yujie Xie, Changrui Chen, Xi

Zdroj: Journal of Process Control. Aug2025, Vol. 152, pN.PAG-N.PAG. 1p.

Témata: *GENERATIVE adversarial networks, *LONG short-term memory, *TIME series analysis, *AUTOENCODERS, *LATENT variables, *SUPERVISED learning

Semi-supervised method for tunnel blasting quality prediction using measurement while drilling data

Autoři: Hengxiang Jin Qian Fang Jun Wang a další

Zdroj: Journal of Rock Mechanics and Geotechnical Engineering, Vol 17, Iss 5, Pp 2633-2649 (2025)

Témata: Semi-supervised learning, Measurement while drilling (MWD), TA703-712, Engineering geology. Rock mechanics. Soil mechanics. Underground construction, Over/under excavation, Tunnel blasting quality

Přístupová URL adresa: https://doaj.org/article/36306ea7c4f34e8283f27b96db764e1a

A semi-supervised autoencoder framework for joint generation and classification of breathing.

Autoři: Pastor-Serrano, Oscar Lathouwers, Danny Perkó, Zoltán

Zdroj: Computer Methods & Programs in Biomedicine. Sep2021, Vol. 209, pN.PAG-N.PAG. 1p.

Témata: *COMPUTER-aided diagnosis, *CONVOLUTIONAL neural networks, *RESPIRATION, *ALGORITHMS, *TIME series analysis