Suchergebnisse - Stacked denoising convolution autoencoder*

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

Autoren: Naga Prasanthi Yerneni V.S. Ghali G.T. Vesala et al.

Quelle: Infrared Physics & Technology. 143:105612

Intelligent fault diagnosis method of rolling bearing based on stacked denoising autoencoder and convolutional neural network

Autoren: Changchang Che Xiaomei Ni Qiang Fu et al.

Quelle: Industrial Lubrication and Tribology. 72:947-953

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

Zugangs-URL: https://www.emerald.com/insight/content/doi/10.1108/ILT-11-2019-0496/full/html

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

Autoren: Zhang, Chengyi Yu, Jianbo Wang, Shijin

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

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

Anomaly Detection Through Deep Feature Extraction for Automatic Defect Detection in Quadratic Frequency Modulated Thermal Wave Imaging.

Autoren: Yerneni, Naga Prasanthi Ghali, V. S. Swapna, M. N. et al.

Quelle: Russian Journal of Nondestructive Testing. Apr2025, Vol. 61 Issue 4, p481-489. 9p.

Schlagwörter: *DEEP learning, *AUTOENCODERS, *FEATURE extraction, *OUTLIER detection, *DEFECT tracking (Computer software development), *THERMOGRAPHY

Physics-Informed SDAE-Based Denoising Model for High-Impedance Fault Detection.

Autoren: Lin, Jianxin Wang, Xuchang Wang, Huaiyuan

Quelle: Processes; Nov2025, Vol. 13 Issue 11, p3673, 23p

Schlagwörter: FAULT diagnosis, SIGNAL denoising, SIGNAL integrity (Electronics), ELECTRIC power distribution, SIGNAL processing, DISCRETE wavelet transforms

PARKINSON'S DISEASE CLASSIFICATION BASED ON STACKED DENOISING AUTOENCODER.

Autoren: SUKANYA, P. RAO, B. SRINIVASA

Quelle: Computer Science; 2023, Vol. 24 Issue 4, p491-512, 22p

Schlagwörter: NOSOLOGY, PARKINSON'S disease, BRAIN degeneration, NEUROLOGICAL disorders, DEEP brain stimulation, DATA augmentation

Intelligent fault diagnosis method of rolling bearing based on stacked denoising autoencoder and convolutional neural network.

Autoren: Che, Changchang Wang, Huawei Ni, Xiaomei et al.

Quelle: Industrial Lubrication & Tribology; 2020, Vol. 72 Issue 7, p947-953, 7p

Schlagwörter: CONVOLUTIONAL neural networks, FAULT diagnosis, ROLLER bearings, DIAGNOSIS, TIME series analysis, GOLGI apparatus

Visual saliency detection via invariant feature constrained stacked denoising autoencoder.

Autoren: Ma, Yunpeng Yu, Zhihong Zhou, Yaqin et al.

Quelle: Multimedia Tools & Applications; Jul2023, Vol. 82 Issue 18, p27451-27472, 22p

Schlagwörter: PROBLEM solving, AUTOMORPHISMS, IMAGE reconstruction algorithms

Stacked denoising autoencoder for missing traffic data reconstruction via mobile edge computing.

Autoren: Dai, Penglin Luo, Jingtao Zhao, Kangli et al.

Quelle: Neural Computing & Applications; Jul2023, Vol. 35 Issue 19, p14259-14274, 16p

Schlagwörter: MOBILE computing, EDGE computing, DEEP learning, CLOUD computing, ALGORITHMS, ORTHOGONAL matching pursuit

Gender Identification Using Marginalised Stacked Denoising Autoencoders on Twitter Data.

Autoren: Al-onazi, Badriyya B. Nour, Mohamed K. Alshamrani, Hassan et al.

Quelle: Intelligent Automation & Soft Computing; 2023, Vol. 36 Issue 3, p2529-2544, 16p

Schlagwörter: GENDER differences (Sociology)

Firma/Körperschaft: X Corp.

Matrix factorization with denoising autoencoders for prediction of drug-target interactions.

Autoren: Sajadi SZ Zare Chahooki MA Tavakol M et al.

Quelle: Molecular diversity [Mol Divers] 2023 Jun; Vol. 27 (3), pp. 1333-1343. Date of Electronic Publication: 2022 Jul 23.

Publikationsart: Journal Article

Info zur Zeitschrift: Publisher: ESCOM Science Publishers Country of Publication: Netherlands NLM ID: 9516534 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1573-501X (Electronic) Linking ISSN: 13811991 NLM ISO Abbreviation: Mol Divers Subsets: MEDLINE

MeSH-Schlagworte: Algorithms* , Machine Learning*, Drug Interactions ; Research Design ; ROC Curve

Deep feature fusion‐based stacked denoising autoencoder for tag recommendation systems.

Autoren: Fei, Zhengshun Wang, Jinglong Liu, Kangling et al.

Quelle: IET Cyber-systems & Robotics; Sep2023, Vol. 5 Issue 3, p1-16, 16p

Segmentation‐enhanced gamma spectrum denoising based on deep learning.

Autoren: Lu, Xiangqun Zheng, Hongzhi Liu, Yaqiong et al.

Quelle: IET Communications (Wiley-Blackwell); Jan2024, Vol. 18 Issue 1, p63-80, 18p

Schlagwörter: DEEP learning, HILBERT-Huang transform, GAMMA-ray scattering, ELECTRONIC noise, FEATURE extraction

Ground Target Recognition Using Carrier-Free UWB Radar Sensor With a Semi-Supervised Stacked Convolutional Denoising Autoencoder.

Autoren: Zhu, Yuying Zhang, Shuning Li, Xiaoxiong et al.

Quelle: IEEE Sensors Journal; 9/15/2021, Vol. 21 Issue 18, p20685-20693, 9p

A novel multimodal framework for automatic recognition of individual cattle based on hybrid features using sparse stacked denoising autoencoder and group sparse representation techniques.

Autoren: Kumar, Santosh Kumar, Sunil Shafi, Mehak et al.

Quelle: Multimedia Tools & Applications; Sep2022, Vol. 81 Issue 21, p31075-31106, 32p

Schlagwörter: ENDANGERED species, FEATURE extraction, FACE, EXTRACTION techniques

Video surveillance image enhancement via a convolutional neural network and stacked denoising autoencoder.

Autoren: Che Aminudin, Muhamad Faris Suandi, Shahrel Azmin

Quelle: Neural Computing & Applications; Feb2022, Vol. 34 Issue 4, p3079-3095, 17p

Schlagwörter: CONVOLUTIONAL neural networks, HUMAN facial recognition software, VIDEO surveillance, IMAGE intensifiers, SIGNAL-to-noise ratio, IMAGE fusion, DEEP learning, VIDEO codecs

Intelligent Diagnosis of Subway Traction Motor Bearing Fault Based on Improved Stacked Denoising Autoencoder.

Autoren: Xu, Yanwei Li, Chen Xie, Tancheng

Quelle: Shock & Vibration; 1/12/2021, p1-9, 9p

Schlagwörter: TRACTION motors, FAULT diagnosis, SUBWAYS, SIGNAL processing, FEATURE extraction, DEEP learning, BRIDGE bearings

An Analog Circuit Fault Diagnosis Method Incorporating Multi-Objective Selection of Measurement Nodes.

Autoren: Chang, Yating Xu, Xianglian Deng, Kaitian et al.

Quelle: Electronics (2079-9292); Apr2025, Vol. 14 Issue 8, p1528, 21p

Schlagwörter: FAULT diagnosis, AUTOENCODERS, CLASSIFICATION algorithms, ELECTRONIC equipment, PARTICLE swarm optimization, ANALOG circuits, INFORMATION measurement

Automatic Detection of COVID-19 Using a Stacked Denoising Convolutional Autoencoder.

Autoren: Dhahri, Habib Rabhi, Besma Chelbi, Slaheddine et al.

Quelle: Computers, Materials & Continua; 2021, Vol. 69 Issue 3, p3259-3274, 16p

Schlagwörter: COVID-19, SARS-CoV-2, CAUSES of death, PHYSICIANS, X-ray imaging, COVID-19 testing

Multi-lingual handwriting recovery framework based on convolutional denoising autoencoder with attention model.

Autoren: Rabhi, Besma Elbaati, Abdelkarim Boubaker, Houcine et al.

Quelle: Multimedia Tools & Applications; Mar2024, Vol. 83 Issue 8, p22295-22326, 32p