Search Results - Stacked denoising convolution autoencoder~

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

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

Source: Infrared Physics & Technology. 143:105612

Enhanced defect detection in thermography through temporal denoising and deep feature extraction using a shallow convolution autoencoder

Authors: Y Naga Prasanthi V S Ghali G T Vesala et al.

Source: Insight - Non-Destructive Testing and Condition Monitoring. 67:162-171

Gaussian Mixture with Max Expectation Guide for Stacked Architecture of Denoising Autoencoder and DRBM for Medical Chest Scans and Disease Identification

Authors: Mona Jamjoom Abeer M. Mahmoud Safia Abbas et al.

Source: Electronics; Volume 12; Issue 1; Pages: 105

Subject Terms: 03 medical and health sciences, 0302 clinical medicine, deep learning, pneumonia prediction, Gaussian mixture, convolution autoencoder, Boltzmann machine, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology, 3. Good health

File Description: application/pdf

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

Authors: Changchang Che Xiaomei Ni Qiang Fu et al.

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

Subject Terms: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Access 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.

Authors: Zhang, Chengyi Yu, Jianbo Wang, Shijin

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

Subject Terms: *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.

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

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

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

Enhanced defect detection in thermography through temporal denoising and deep feature extraction using a shallow convolution autoencoder.

Authors: Prasanthi, Y. Naga Ghali, V. S. Vesala, G. T. et al.

Source: Insight: Non-Destructive Testing & Condition Monitoring; Mar2025, Vol. 67 Issue 3, p162-171, 10p

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

Authors: Lin, Jianxin Wang, Xuchang Wang, Huaiyuan

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

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

A QUANTUM CONVOLUTION AUTOENCODER FOR HANDWRITTEN LETTERS AND DIGITS: A CASE STUDY.

Authors: SAWERWAIN, MAREK KOWAL, MAREK KORBICZ, JÓZEF

Source: International Journal of Applied Mathematics & Computer Science; 2025, Vol. 35 Issue 4, p651-666, 16p

PARKINSON'S DISEASE CLASSIFICATION BASED ON STACKED DENOISING AUTOENCODER.

Authors: SUKANYA, P. RAO, B. SRINIVASA

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

Subject Terms: 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.

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

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

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

Visual saliency detection via invariant feature constrained stacked denoising autoencoder.

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

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

Subject Terms: PROBLEM solving, AUTOMORPHISMS, IMAGE reconstruction algorithms

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

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

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

Publication Type: Journal Article

Journal Info: 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 Terms: Algorithms* , Machine Learning*, Drug Interactions ; Research Design ; ROC Curve

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

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

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

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

Gender Identification Using Marginalised Stacked Denoising Autoencoders on Twitter Data.

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

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

Subject Terms: GENDER differences (Sociology)

Company/Entity: X Corp.

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

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

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

Segmentation‐enhanced gamma spectrum denoising based on deep learning.

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

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

Subject Terms: 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.

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

Source: 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.

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

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

Subject Terms: ENDANGERED species, FEATURE extraction, FACE, EXTRACTION techniques

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

Authors: Che Aminudin, Muhamad Faris Suandi, Shahrel Azmin

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

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