Výsledky vyhledávání - deep denoising autoencoder*

Conditioned fully convolutional denoising autoencoder for multi-target NILM

Autoři: García, Diego Pérez, Daniel Papapetrou, Panagiotis a další

Zdroj: Neural Computing & Applications. 37(17):10491-10505

Témata: Non-intrusive Load Monitoring, Energy Efficiency, Deep Convolutional Neural Networks, Interpretability, Multi-target NILM models, data- och systemvetenskap, Computer and Systems Sciences

Popis souboru: print

Přístupová URL adresa: https://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-237967
https://doi.org/10.1007/s00521-024-10552-0

Predicting protein–protein interactions in microbes associated with cardiovascular diseases using deep denoising autoencoders and evolutionary information

Autoři: Senyu Zhou Jian Luo Mei Tang a další

Zdroj: Front Pharmacol
Frontiers in Pharmacology, Vol 16 (2025)

Témata: Pharmacology, CatBoost, cardiovascular disease, evolutionary information, protein–protein interactions, Therapeutics. Pharmacology, RM1-950, deep denoising autoencoder

Přístupová URL adresa: https://pubmed.ncbi.nlm.nih.gov/40135232
https://doaj.org/article/dfbaf48dbdb74080bd34cd4b29f4c845

DDANF: Deep denoising autoencoder normalizing flow for unsupervised multivariate time series anomaly detection

Autoři: Xigang Zhao Peng Liu Saïd Mahmoudi a další

Zdroj: Alexandria Engineering Journal, Vol 108, Iss, Pp 436-444 (2024)

Témata: Time series, Normalizing flow, 0202 electrical engineering, electronic engineering, information engineering, Anomaly detection, Autoencoder, 02 engineering and technology, TA1-2040, Engineering (General). Civil engineering (General)

Přístupová URL adresa: https://doaj.org/article/e210902e3c384e91a1fcd8c59dbacd0b

A Novel PAPR Reduction Scheme Based on Deep Autoencoder Network for FBMC Systems

Autoři: Xing Cheng Deli Chen Shuaishuai Li a další

Zdroj: IEEE Access, Vol 13, Pp 68948-68958 (2025)

Témata: peak to average power ratio, denoising autoencoder network, deep learning, Filter bank multicarrier, Electrical engineering. Electronics. Nuclear engineering, TK1-9971

Přístupová URL adresa: https://doaj.org/article/678c4448230241fc87fe49f3e61edf69

Intelligent back-to-back testing with denoising autoencoder-based fault detection and DBSCAN clustering

Autoři: Mohammad Abboush Christoph Knieke Andreas Rausch

Zdroj: Results in Engineering, Vol 27, Iss, Pp 105900-(2025)

Témata: Fault detection and clustering, Technology, Back-to-back testing, Deep denoising autoencoder, HIL testing, Real-time validation, Automotive software systems

Přístupová URL adresa: https://doaj.org/article/34c5052e622c4cb18ed2d1499b7ffeea

Enhancing Sound-Based Anomaly Detection Using Deep Denoising Autoencoder

Autoři: Seong-Mok Kim Yong Soo Kim

Zdroj: IEEE Access, Vol 12, Pp 84323-84332 (2024)

Témata: machine learning, feature extraction, 0202 electrical engineering, electronic engineering, information engineering, Electrical engineering. Electronics. Nuclear engineering, 02 engineering and technology, fault diagnosis, 01 natural sciences, anomaly detection, Acoustic signal processing, automation, TK1-9971, 0104 chemical sciences

Přístupová URL adresa: https://doaj.org/article/f68405dcd372477890d80807f5899e82

Stealthy data integrity attack identification in smart grid networks utilizing deep denoising autoencoder

Autoři: Anila Kousar Saeed Ahmed Abdullah Altamimi a další

Zdroj: Heliyon, Vol 10, Iss 19, Pp e38470- (2024)

Témata: Cyber-physical systems, Cyber assaults, Smart grids, State estimation, Deep denoising autoencoder, Machine learning, Science (General), Q1-390, Social sciences (General), H1-99

Popis souboru: electronic resource

Relation: http://www.sciencedirect.com/science/article/pii/S240584402414501X; https://doaj.org/toc/2405-8440

Přístupová URL adresa: https://doaj.org/article/a335d3e7b3184d5da05214ba21691b56

Automated computer-aided design of cranial implants using a deep volumetric convolutional denoising autoencoder

Autoři: Morais, Ana Egger, Jan Alves, Victor a další

Přispěvatelé: Morais, Ana Egger, Jan Alves, Victor a další

Témata: 3D shape completion, Computer-aided design (CAD), Cranial implant, Deep learning, Denoising autoencoder, Medical imaging

Popis souboru: application/pdf

Relation: 978-3-030-16186-6; 2194-5357

Dostupnost: https://hdl.handle.net/1822/71391

A Network Intrusion Detection Framework on Sparse Deep Denoising Autoencoder for Dimensionality Reduction

Autoři: B. A. Manjunatha K. Aditya Shastry E. Naresh a další

Zdroj: Soft Computing. 28:4503-4517

Deep Denoising Convolutional Autoencoder-Based Fault Diagnosis of A Centrifugal Pump

Autoři: Daniyal Maroufi Ali Sadighi

Zdroj: 2023 11th RSI International Conference on Robotics and Mechatronics (ICRoM). :550-555

Denoising Autoencoder, A Deep Learning Algorithm, Aids the Identification of A Novel Molecular Signature of Lung Adenocarcinoma

Autoři: Wang, Jun Xie, Xueying Shi, Junchao a další

Zdroj: Genomics Proteomics & Bioinformatics. 18(4)

Témata: Information and Computing Sciences, Machine Learning, Clinical Research, Cancer, Lung Cancer, Lung, Rare Diseases, Genetics, 4.1 Discovery and preclinical testing of markers and technologies, Detection, screening and diagnosis, Good Health and Well Being, Adenocarcinoma of Lung, Algorithms, Deep Learning, Humans, Lung Neoplasms, Transcriptome, Denoising autoencoder, Unsupervised learning, Lung cancer, Prognosis, Molecular signature, Mathematical Sciences, Biological Sciences, Bioinformatics, Biological sciences, Information and computing sciences, Mathematical sciences

Popis souboru: application/pdf

Přístupová URL adresa: https://escholarship.org/uc/item/91b109pq
https://escholarship.org/content/qt91b109pq/qt91b109pq.pdf

Speech Intelligibility Enhancement for Cochlear Implant using Multi-Objective Deep Denoising Autoencoder

Autoři: Barre Uma Prasanna Vishnu Venkateswarlu Poluboina Sushma B a další

Zdroj: 2023 IEEE 20th India Council International Conference (INDICON). :173-178

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

Autoři: Kurmi Y Viswanathan M Zu Z

Zdroj: Magnetic resonance in medicine [Magn Reson Med] 2024 Dec; Vol. 92 (6), pp. 2404-2419. Date of Electronic Publication: 2024 Jul 19.

Způsob vydávání: Journal Article

Informace o časopise: Publisher: Wiley Country of Publication: United States NLM ID: 8505245 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1522-2594 (Electronic) Linking ISSN: 07403194 NLM ISO Abbreviation: Magn Reson Med Subsets: MEDLINE

Výrazy ze slovníku MeSH: Deep Learning* , Signal-To-Noise Ratio* , Magnetic Resonance Imaging*/methods , Image Processing, Computer-Assisted*/methods , Phantoms, Imaging*, Animals ; Mice ; Algorithms ; Principal Component Analysis

Random noise attenuation of ocean bottom seismometers based on a substep deep denoising autoencoder

Autoři: Haoran Lin Jian Xu Lei Xing a další

Zdroj: Geophysical Prospecting. 72:1428-1441

Témata: 14. Life underwater, 01 natural sciences, 0105 earth and related environmental sciences

Improving Speech Quality for Hearing Aid Applications Based on Wiener Filter and Composite of Deep Denoising Autoencoders

Autoři: Raghad Yaseen Lazim Zhu Yun Xiaojun Wu

Zdroj: Signals
Volume 1
Issue 2
Pages 8-156

Témata: noise reduction, 03 medical and health sciences, Wiener filter, 0103 physical sciences, speech enhancement, 0305 other medical science, 01 natural sciences, hearing aids, deep denoising autoencoder

Popis souboru: application/pdf

Přístupová URL adresa: https://www.mdpi.com/2624-6120/1/2/8/pdf
https://www.mdpi.com/2624-6120/1/2/8/pdf
https://www.mdpi.com/2624-6120/1/2/8

Environmental Noise Reduction based on Deep Denoising Autoencoder

Autoři: A. Azmat I. Ali W. Ariyanti a další

Zdroj: Engineering, Technology & Applied Science Research. 12:9532-9535

Témata: 03 medical and health sciences, 0305 other medical science

DDSA: A Defense Against Adversarial Attacks Using Deep Denoising Sparse Autoencoder

Autoři: Yassine Bakhti Sid Ahmed Fezza Wassim Hamidouche a další

Přispěvatelé: Yassine Bakhti Sid Ahmed Fezza Wassim Hamidouche a další

Zdroj: IEEE Access, Vol 7, Pp 160397-160407 (2019)

Témata: [INFO.INFO-NE] Computer Science [cs]/Neural and Evolutionary Computing [cs.NE], security, 02 engineering and technology, [INFO.INFO-NE]Computer Science [cs]/Neural and Evolutionary Computing [cs.NE], Deep neural network, TK1-9971, defense, [INFO.INFO-CR]Computer Science [cs]/Cryptography and Security [cs.CR], adversarial attacks, sparse autoencoder, denoising, 0202 electrical engineering, electronic engineering, information engineering, Electrical engineering. Electronics. Nuclear engineering, [INFO.INFO-CR] Computer Science [cs]/Cryptography and Security [cs.CR]

Popis souboru: application/pdf

Přístupová URL adresa: https://ieeexplore.ieee.org/ielx7/6287639/8600701/08890816.pdf
https://doaj.org/article/ccf330a743dd4252a28c82c0c42ec956
https://univ-rennes.hal.science/hal-02349625v1/document
https://doi.org/10.1109/access.2019.2951526
https://univ-rennes.hal.science/hal-02349625v1

DDANF: Deep denoising autoencoder normalizing flow for unsupervised multivariate time series anomaly detection

Autoři: Zhao, Xigang Liu, Peng Mahmoudi, Saïd a další

Témata: Article publié dans une revue, révisé par les pairs, Non évalué par les pairs

URL: https://espace2.etsmtl.ca/id/eprint/29368/
https://doi.org/10.1016/j.aej.2024.07.013
https://espace2.etsmtl.ca/id/eprint/29368
https://doi.org/10.1016/j.aej.2024.07.013
10.1016/j.aej.2024.07.013

A Modular Deep Denoising Autoencoder for speech enhancement

Autoři: Raghad Yaseen Lazim Al-Taai Xiaojun Wu

Zdroj: 2022 3rd International Conference for Emerging Technology (INCET). :1-6

Convolutional deep denoising autoencoders for radio astronomical images

Autoři: C. Gheller Franco Vazza

Zdroj: Monthly Notices of the Royal Astronomical Society

Témata: FOS: Computer and information sciences, Computer Science - Machine Learning, intergalactic medium, large-scale structure of Universe, methods, numerical, 0103 physical sciences, FOS: Physical sciences, Astrophysics - Instrumentation and Methods for Astrophysics, Instrumentation and Methods for Astrophysics (astro-ph.IM), 01 natural sciences, Machine Learning (cs.LG)

Popis souboru: application/pdf

Přístupová URL adresa: http://arxiv.org/pdf/2110.08618
http://arxiv.org/abs/2110.08618
https://dblp.uni-trier.de/db/journals/corr/corr2110.html#abs-2110-08618
https://arxiv.org/abs/2110.08618
https://academic.oup.com/mnras/article/509/1/990/6408492
https://doi.org/10.1093/mnras/stab3044
https://hdl.handle.net/11585/850554