Search Results - Convolutional denoising autoencoder*

Conditioned fully convolutional denoising autoencoder for multi-target NILM

Authors: García, Diego Pérez, Daniel Papapetrou, Panagiotis et al.

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

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

File Description: print

Access URL: 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

Authors: Gianluca Rho Nicola Carbonaro Marco Laurino et al.

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

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

File Description: application/pdf

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

Authors: Asri Rizki Yuliani Hilman Ferdinandus Pardede Ade Ramdan et al.

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

Subject Terms: 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

Access URL: https://doaj.org/article/045065a2412848b69e82bedb7c7174af

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

Authors: Jing REN Xiuhui TAN Yanping BAI et al.

Source: 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

Authors: Xufeng Zhao Ying Chen Mengshu Yang et al.

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

Overcomplete graph convolutional denoising autoencoder for noisy skeleton action recognition

Authors: Jiajun Guo Qingge Ji Guangwei Shan

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

Subject Terms: 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

Access URL: https://doaj.org/article/00b9628a0619472cb07d01a0acb202f8

A Comparative Study on Denoising from Facial Images Using Convolutional Autoencoder

Authors: Muazzez Buket DARICI Zeki ERDEM

Source: Volume: 36, Issue: 3 1122-1138
Gazi University Journal of Science

Subject Terms: Facial images, Mühendislik, Gaussian distribution, Optimizers, 02 engineering and technology, Gaussian noise, Salt and pepper noise, 03 medical and health sciences, Engineering, 0302 clinical medicine, Median filters, De-noising, Evaluation metrics, 0202 electrical engineering, electronic engineering, information engineering, Salt-Pepper noise, Denoising, Image segmentation, Signal to noise ratio, Autoencoder, Salt&pepper noise, Learning systems, Auto encoders, Deep learning, Peak signal to noise ratio, Structural similarity, Convolution, Gaussians, Gaussian noise (electronic)

File Description: application/pdf

Access URL: https://hdl.handle.net/20.500.12469/4859
https://dergipark.org.tr/tr/pub/gujs/issue/79068/1051655

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

Authors: Meng Chen Yongjian Li Liting Zhang et al.

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

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

Access URL: https://pubmed.ncbi.nlm.nih.gov/38241105

Optimizing Medical Image Quality Through Hybrid Machine Learning Techniques and Convolutional Denoising Autoencoders

Authors: Manoj Kumar Singh Vaishali Bhargava Nidhi Sharma et al.

Source: Springer Series in Reliability Engineering ISBN: 9783031987274

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

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

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

Physical Layer Authentication for Industrial Control Based on Convolutional Denoising Autoencoder

Authors: Yanru Chen Haoyu He Shengjie Liu et al.

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

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

Authors: Fahimeh Mohagheghian Dong Han Om Ghetia et al.

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

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

Access URL: https://pubmed.ncbi.nlm.nih.gov/37682653

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

Authors: M. Rajalakshmi R. S. Sankara Subramanian S. Tamilselvan et al.

Source: International Journal of Information Technology.

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

Authors: Gianluca Rho Nicola Carbonaro Marco Laurino et al.

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

Authors: Raktim Acharjee Shaik Rafi Ahamed

Source: 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

Authors: Morais, Ana Egger, Jan Alves, Victor et al.

Contributors: Morais, Ana Egger, Jan Alves, Victor et al.

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

File Description: application/pdf

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

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

Lung Disease Classification in Chest X-Rays with Feature Fusion via Stacked Convolutional Denoising Autoencoders

Authors: Jutika Borah Hidam Kumarjit Singh Kumaresh Sarmah

Source: 2023 IEEE International Conference on Computer Vision and Machine Intelligence (CVMI). :1-6

Galaxy Model Subtraction with a Convolutional Denoising Autoencoder

Authors: Liu, Rongrong Peng, Eric W. Wang, Kaixiang et al.

Subject Terms: Astrophysics of Galaxies, Instrumentation and Methods for Astrophysics

Access URL: http://arxiv.org/abs/2510.04957

Radar modulation recognition based on convolutional denoising autoencoder

Authors: Jie Yang Yaoxiang Hui Junpeng Zhu

Source: 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

Authors: Jyostna Devi Bodapati Bharadwaj Bagepalli Balaji

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