Výsledky vyhledávání - sparse convolutional autoencoder (((sace OR sae) OR sage))

基于改进生成对抗网络和 Swin Transformer 的样本不均衡轴承故障诊断.

Alternate Title: Bearing fault diagnosis based on improved generative adversarial network and Swin Transformer under imbalanced sample conditions.

Autoři: 马良玉 黄日灏 段晓冲 a další

Zdroj: Journal of Nanjing University of Information Science & Technology (Natural Science Edition) / Nanjing Xinxi Gongcheng Daxue Xuebao (ziran kexue ban). Jul2025, Vol. 17 Issue 4, p528-537. 10p.

Témata: *Transformer models, Convolutional neural networks, Generative adversarial networks, Fault diagnosis, Deep learning

Out-of-Roundness Wheel Damage Identification in Railway Vehicles Using AutoEncoder Models

Autoři: Renato Melo Rafaelle Finotti António Guedes a další

Zdroj: Applied Sciences ; Volume 15 ; Issue 5 ; Pages: 2662

Témata: structural health monitoring, railways, damage detection, out of roundness, sparse autoencoder, convolutional autoencoder, variational autoencoder

Geografické téma: agris

Popis souboru: application/pdf

Relation: Civil Engineering; https://dx.doi.org/10.3390/app15052662

Dostupnost: https://doi.org/10.3390/app15052662

Industrial Internet of Things Cyber Threats Detection Through Deep Feature Learning and Stacked Sparse Autoencoder Based Classification

Autoři: R. Vijay Anand G. Magesh I. Alagiri a další

Zdroj: Transactions on Emerging Telecommunications Technologies. 36

The Missing Curve Detectors of InceptionV1: Applying Sparse Autoencoders to InceptionV1 Early Vision

Autoři: Gorton, Liv

Témata: Computer Science - Machine Learning, text

URL: http://arxiv.org/abs/2406.03662

Type 2 diabetes prediction method based on dual-teacher knowledge distillation and feature enhancement.

Autoři: Zhao, Jian Gao, Hanlin Sun, Lei a další

Zdroj: Scientific Reports. 1/2/2025, Vol. 15 Issue 1, p1-15. 15p.

Témata: *CONVOLUTIONAL neural networks, *TYPE 2 diabetes, *AUTOENCODERS, *MEDICAL care costs, *DIABETES

Diagnosis of unbalanced bearing fault samples based on cycle generative adversarial networks.

Autoři: Huang, Rihao Ma, Liangyu Hu, Jingchen a další

Zdroj: Neural Computing & Applications. Jul2025, Vol. 37 Issue 19, p13447-13467. 21p.

Témata: *CONVOLUTIONAL neural networks, *TRANSFORMER models, *GENERATIVE adversarial networks, *ARTIFICIAL intelligence, *FAULT diagnosis, *ROLLER bearings

Sparse convolutional autoencoder‐based fault location for drive circuits in nuclear reactors.

Autoři: Yang, Cheng Yuan, Yannan Wang, Fu a další

Zdroj: Quality & Reliability Engineering International; Mar2024, Vol. 40 Issue 2, p819-837, 19p

Témata: FAULT location (Engineering), NUCLEAR reactors, NUCLEAR reactor control, FAULT diagnosis, ELECTRONIC equipment, LINE drivers (Integrated circuits)

Out-of-roundness damage wheel idenficaon in railway vehicles using autoencoder models

Autoři: Melo, Renato da Silva Cury, Alexandre Abrahão http://lattes.cnpq.br/1092810690505352 a další

Přispěvatelé: Melo, Renato da Silva Cury, Alexandre Abrahão http://lattes.cnpq.br/1092810690505352 a další

Témata: Monitoramento de integridade estrutural, Ferrovias, Detecção de danos, Ovalização, Autocodificador esparso, Autocodificador convolucional, Autocodificador variacional, Structural health monitoring, Railways, Damage detection, Out-of-roundness, Sparse autoencoder, Convolutional autoencoder, Variational autoencoder, CNPQ::ENGENHARIAS

Popis souboru: application/pdf

Relation: https://repositorio.ufjf.br/jspui/handle/ufjf/18552

Dostupnost: https://repositorio.ufjf.br/jspui/handle/ufjf/18552

Deep Learning-Based Magnetic Resonance Image Segmentation and Classification for Alzheimer's Disease Diagnosis.

Autoři: Manochandar, T. Diderot, P. Kumaraguru

Zdroj: International Journal of Image & Graphics. May2025, Vol. 25 Issue 3, p1-17. 17p.

Témata: *CONVOLUTIONAL neural networks, *IMAGE analysis, *IMAGE recognition (Computer vision), *IMAGE segmentation, *ALZHEIMER'S disease

Application of Artificial Intelligence Technologies as an Intervention for Promoting Healthy Eating and Nutrition in Older Adults: A Systematic Literature Review.

Autoři: Kalu, Kingsley Ataguba, Grace Onifade, Oyepeju a další

Zdroj: Nutrients. Oct2025, Vol. 17 Issue 20, p3223. 33p.

Automated Video-EEG Analysis in Epilepsy Studies: A Narrative Review of Advances and Challenges.

Autoři: Zuev VA Salmagambetova EG Djakov SN a další

Zdroj: Journal of medical systems [J Med Syst] 2025 Oct 20; Vol. 49 (1), pp. 142. Date of Electronic Publication: 2025 Oct 20.

Způsob vydávání: Journal Article; Review

Informace o časopise: Publisher: Kluwer Academic/Plenum Publishers Country of Publication: United States NLM ID: 7806056 Publication Model: Electronic Cited Medium: Internet ISSN: 1573-689X (Electronic) Linking ISSN: 01485598 NLM ISO Abbreviation: J Med Syst Subsets: MEDLINE

Výrazy ze slovníku MeSH: Electroencephalography*/methods , Epilepsy*/diagnosis , Epilepsy*/physiopathology , Video Recording*/methods, Humans ; Machine Learning

Hyperspectral Image: A Fusion-Based Extraction and Classification Utilizing Centernet Technique.

Autoři: Rajyalakshmi, Ch Sanjeevaiah, K. Jose, Bibin K a další

Zdroj: International Journal of Image & Graphics. Jun2025, p1. 28p.

Témata: *HYPERSPECTRAL imaging systems, *DEEP learning, *IMAGE recognition (Computer vision), *CENTROID, *ARTIFICIAL neural networks, *AUTOENCODERS, *FEATURE extraction

Investigating Beta-Variational Convolutional Autoencoders for the Unsupervised Classification of Chest Pneumonia.

Autoři: Akila, Serag Mohamed Imanov, Elbrus Almezhghwi, Khaled

Zdroj: Diagnostics (2075-4418); Jul2023, Vol. 13 Issue 13, p2199, 14p

Témata: MACHINE learning, PNEUMONIA, ANOMALY detection (Computer security), LUNG infections, DIAGNOSIS, KLEBSIELLA infections

Towards COVID-19 detection and classification using optimal efficient Densenet model on chest X-ray images.

Autoři: Hilali-Jaghdam, Inès Elhag, Azhari A. Ben Ishak, Anis a další

Zdroj: Alexandria Engineering Journal. Aug2024, Vol. 101, p136-146. 11p.

Témata: Optimization algorithms, COVID-19 pandemic, Convolutional neural networks, Deep learning, Polymerase chain reaction, X-rays

Shelf Commodity Identification Method Based on Hybrid Fully Convolutional Automatic Encoder

Autoři: Aofeng Cheng Guodong Chen Zheng Wang

Zdroj: IEEE Access, Vol 7, Pp 169899-169907 (2019)

Témata: Fully convolutional neural network, autoencoder, object identification, shelf regulation, Electrical engineering. Electronics. Nuclear engineering, TK1-9971

Popis souboru: electronic resource

Relation: https://ieeexplore.ieee.org/document/8911324/; https://doaj.org/toc/2169-3536

Přístupová URL adresa: https://doaj.org/article/430ef5e3edfc4c1d8c85e459deb5fba4

EEG-Based Emotion Classification Using a Deep Neural Network and Sparse Autoencoder

Autoři: Junxiu Liu Guopei Wu Yuling Luo a další

Zdroj: Frontiers in Systems Neuroscience, Vol 14 (2020)

Témata: EEG, emotion recognition, convolutional neural network, sparse autoencoder, deep neural network, Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571

Popis souboru: electronic resource

Relation: https://www.frontiersin.org/article/10.3389/fnsys.2020.00043/full; https://doaj.org/toc/1662-5137

Přístupová URL adresa: https://doaj.org/article/418867ee4c3d4faebc2345d057d410f5

Structural Damage Identification Using Autoencoders: A Comparative Study

Autoři: Marcos Spínola Neto Rafaelle Finotti Flávio Barbosa a další

Zdroj: Buildings, Vol 14, Iss 7, p 2014 (2024)

Témata: structural health monitoring, damage detection, autoencoders, sparse, variational, convolutional, Building construction, TH1-9745

Popis souboru: electronic resource

Relation: https://www.mdpi.com/2075-5309/14/7/2014; https://doaj.org/toc/2075-5309

Přístupová URL adresa: https://doaj.org/article/5ca467200dd84878b831d5f1dcdcca9e

Research on Target Object Recognition Based on Transfer-Learning Convolutional SAE in Intelligent Urban Construction

Autoři: Bing Xie Zhemin Duan Bin Zheng a další

Zdroj: IEEE Access, Vol 7, Pp 125357-125368 (2019)

Témata: Target objects recognition, sparse auto-encoder, transfer learning, intelligent urban, Electrical engineering. Electronics. Nuclear engineering, TK1-9971

Popis souboru: electronic resource

Relation: https://ieeexplore.ieee.org/document/8822989/; https://doaj.org/toc/2169-3536

Přístupová URL adresa: https://doaj.org/article/ae9fb781a41042a7a678a78c3d9c2eed

Flight Test Sensor Fault Diagnosis Based on Data-Fusion and Machine Learning Method

Autoři: Hongxin Wang Degang Xu Xin Wen a další

Zdroj: IEEE Access, Vol 10, Pp 120013-120022 (2022)

Témata: Convolutional neural network, fault classification, flight test data, fault diagnosis, sparse autoencoder, Electrical engineering. Electronics. Nuclear engineering, TK1-9971

Popis souboru: electronic resource

Relation: https://ieeexplore.ieee.org/document/9928333/; https://doaj.org/toc/2169-3536

Přístupová URL adresa: https://doaj.org/article/f50ce16502da41ccae03b60fb2048516

Research on a Convolution Kernel Initialization Method for Speeding Up the Convergence of CNN

Autoři: Chunyu Xu Hong Wang

Zdroj: Applied Sciences, Vol 12, Iss 2, p 633 (2022)

Témata: convolutional neural network, convolution kernel, local binary patterns, sparse autoencoder, Technology, Engineering (General). Civil engineering (General), TA1-2040, Biology (General), QH301-705.5, Physics, QC1-999, Chemistry, QD1-999

Popis souboru: electronic resource

Relation: https://www.mdpi.com/2076-3417/12/2/633; https://doaj.org/toc/2076-3417

Přístupová URL adresa: https://doaj.org/article/2284785b658a4daa810370cf9e55fc6e