Výsledky vyhledávání - convolutional 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

Estimating Heart Rate Variability from Wrist-Worn Photoplethysmography Devices in Daily Activities: A Preliminary Convolutional Denoising Autoencoder Approach

Autoři: Gianluca Rho Nicola Carbonaro Marco Laurino a další

Zdroj: 2024 IEEE International Conference on Metrology for eXtended Reality, Artificial Intelligence and Neural Engineering (MetroXRAINE). :207-212

Témata: Wrist , Convolution , Time series analysis , Noise reduction , Autoencoders , Electrocardiography , Photoplethysmography , Reliability , Heart rate variability , Biomedical monitoring

Popis souboru: application/pdf

Robust remaining useful life prediction of lithium-ion battery with convolutional denoising autoencoder

Autoři: Asri Rizki Yuliani Hilman Ferdinandus Pardede Ade Ramdan a další

Zdroj: Journal of Mechatronics, Electrical Power, and Vehicular Technology, Vol 15, Iss 1, Pp 93-104 (2024)

Témata: neural network, remaining useful life (rul), denoising autoencoder (dae), lithium-ion (li-ion) battery, TJ1-1570, system robustness, Electrical engineering. Electronics. Nuclear engineering, Mechanical engineering and machinery, 7. Clean energy, TK1-9971

Přístupová URL adresa: https://doaj.org/article/045065a2412848b69e82bedb7c7174af

Vector Hydrophone DOA Estimation Method Based on Complex⁃Valued Convolutional Denoising Autoencoder Denoising

Autoři: Jing REN Xiuhui TAN Yanping BAI a další

Zdroj: journal of test and measurement technology. 39:475-482

Fault Diagnosis of Rolling Bearing Using Convolutional Denoising Autoencoder and Siamese Neural Network With Small Sample

Autoři: Xufeng Zhao Ying Chen Mengshu Yang a další

Zdroj: IEEE Internet of Things Journal. 12:5233-5244

Overcomplete graph convolutional denoising autoencoder for noisy skeleton action recognition

Autoři: Jiajun Guo Qingge Ji Guangwei Shan

Zdroj: IET Image Processing, Vol 18, Iss 1, Pp 233-246 (2024)

Témata: QA76.75-76.765, convolutional neural nets, signal denoising, graph theory, Photography, 0202 electrical engineering, electronic engineering, information engineering, Computer software, 02 engineering and technology, TR1-1050, computer vision

Přístupová URL adresa: https://doaj.org/article/00b9628a0619472cb07d01a0acb202f8

Elimination of Random Mixed Noise in ECG Using Convolutional Denoising Autoencoder With Transformer Encoder

Autoři: Meng Chen Yongjian Li Liting Zhang a další

Zdroj: IEEE Journal of Biomedical and Health Informatics. 28:1993-2004

Témata: Electrocardiography, Exercise Test, Humans, Signal Processing, Computer-Assisted, Signal-To-Noise Ratio, Artifacts, Algorithms

Přístupová URL adresa: https://pubmed.ncbi.nlm.nih.gov/38241105

Streamlined convolutional denoising autoencoder vibrothermography: Enhanced detection of bonding interface defects within CFRP-steel adhesive structures

Autoři: Yu-Bin Zhang Chang-Hang Xu Peng-Qian Liu

Zdroj: 2024 IEEE Far East NDT New Technology & Application Forum (FENDT). :214-218

Physical Layer Authentication for Industrial Control Based on Convolutional Denoising Autoencoder

Autoři: Yanru Chen Haoyu He Shengjie Liu a další

Zdroj: IEEE Internet of Things Journal. 11:15633-15641

Noise Reduction in Photoplethysmography Signals Using a Convolutional Denoising Autoencoder With Unconventional Training Scheme

Autoři: Fahimeh Mohagheghian Dong Han Om Ghetia a další

Zdroj: IEEE Transactions on Biomedical Engineering. 71:456-466

Témata: Motion, Heart Rate, Atrial Fibrillation, Humans, Signal Processing, Computer-Assisted, Photoplethysmography, Artifacts, Algorithms, Monitoring, Physiologic

Přístupová URL adresa: https://pubmed.ncbi.nlm.nih.gov/37682653

Adaptive Genghis Khan Shark based convolutional denoising autoencoder for quality enhancement of satellite images

Autoři: M. Rajalakshmi R. S. Sankara Subramanian S. Tamilselvan a další

Zdroj: International Journal of Information Technology.

A Convolutional Denoising Autoencoder Approach for Estimating Heart Rate Variability From Wrist Photoplethysmography Devices in Daily Activities

Autoři: Gianluca Rho Nicola Carbonaro Marco Laurino a další

Automatic Eyeblink Artifact Removal from Single Channel EEG Signals Using One-Dimensional Convolutional Denoising Autoencoder

Autoři: Raktim Acharjee Shaik Rafi Ahamed

Zdroj: 2024 International Conference on Computer, Electrical & Communication Engineering (ICCECE). :1-7

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

Galaxy Model Subtraction with a Convolutional Denoising Autoencoder

Autoři: Liu, Rongrong Peng, Eric W. Wang, Kaixiang a další

Témata: Astrophysics of Galaxies, Instrumentation and Methods for Astrophysics

Přístupová URL adresa: http://arxiv.org/abs/2510.04957

Radar modulation recognition based on convolutional denoising autoencoder

Autoři: Jie Yang Yaoxiang Hui Junpeng Zhu

Zdroj: 2023 6th International Conference on Artificial Intelligence and Pattern Recognition (AIPR). :714-719

TumorAwareNet: Deep representation learning with attention based sparse convolutional denoising autoencoder for brain tumor recognition

Autoři: Jyostna Devi Bodapati Bharadwaj Bagepalli Balaji

Zdroj: Multimedia Tools and Applications. 83:22099-22117

Detection of Freezing of Gait Using Unsupervised Convolutional Denoising Autoencoder

Autoři: Mohd Halim Mohd Noor Amril Nazir Mohd Nadhir Ab Wahab a další

Zdroj: IEEE Access, Vol 9, Pp 115700-115709 (2021)

Témata: Artificial intelligence, Biomedical Engineering, Gait Recognition, Health Professions, Physical Therapy, Sports Therapy and Rehabilitation, 02 engineering and technology, unsupervised learning, FOS: Medical engineering, Pattern recognition (psychology), freezing of gait, Engineering, denoising autoencoder, Health Sciences, Machine learning, Image (mathematics), 0202 electrical engineering, electronic engineering, information engineering, Embedded system, Gait, Sensory Feedback, Gait Analysis and Fall Prevention in Elderly, Deep learning, Wearable computer, Autoencoder, Computer science, Dimensionality reduction, TK1-9971, 3. Good health, Gait Recognition for Human Identification, Thresholding, Physical medicine and rehabilitation, Analysis of Electromyography Signal Processing, Physical Sciences, Parkinson's disease, Medicine, Electrical engineering. Electronics. Nuclear engineering, Gait Analysis

Přístupová URL adresa: https://ieeexplore.ieee.org/ielx7/6287639/6514899/09514558.pdf
https://doaj.org/article/34fba6708ae448288f041a3d55b928c7
https://zuscholars.zu.ac.ae/cgi/viewcontent.cgi?article=5464&context=works
https://zuscholars.zu.ac.ae/works/4465/
https://dblp.uni-trier.de/db/journals/access/access9.html#NoorNWO21

Multi-lingual Handwriting Recovery Framework based on Convolutional Denoising Autoencoder with Attention model

Autoři: Besma Rabhi Abdelkarim Elbaati Houcine Boubaker a další

Zdroj: Multimedia Tools and Applications. 83:22295-22326

Radar Signal Intra-Pulse Modulation Recognition Based on Convolutional Denoising Autoencoder and Deep Convolutional Neural Network

Autoři: Zhiyu Qu Wenyang Wang Changbo Hou a další

Zdroj: IEEE Access, Vol 7, Pp 112339-112347 (2019)

Témata: Cohen class time frequency distribution, deep convolutional neural network, 0202 electrical engineering, electronic engineering, information engineering, Electrical engineering. Electronics. Nuclear engineering, 02 engineering and technology, Radar signal recognition, convolutional denoising autoencoder, TK1-9971

Přístupová URL adresa: https://ieeexplore.ieee.org/ielx7/6287639/8600701/08798607.pdf
https://doaj.org/article/fa33e26e05ce42fbade007ceabff40d1
https://ieeexplore.ieee.org/document/8798607
https://dblp.uni-trier.de/db/journals/access/access7.html#QuWHH19
https://doaj.org/article/fa33e26e05ce42fbade007ceabff40d1
https://doi.org/10.1109/ACCESS.2019.2935247