Výsledky vyhľadávania - sparse convolutional autoencoder ((((scae OR sae) OR sage) OR cae))~

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

Autori: Yang, Cheng Yuan, Yannan Wang, Fu a ďalší

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

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

SCAE—Stacked Convolutional Autoencoder for Fault Diagnosis of a Hydraulic Piston Pump with Limited Data Samples.

Autori: Eraliev, Oybek Lee, Kwang-Hee Lee, Chul-Hee

Zdroj: Sensors (14248220); Jul2024, Vol. 24 Issue 14, p4661, 17p

Predmety: RECIPROCATING pumps, FAULT diagnosis, HIERARCHICAL Bayes model, CONVOLUTIONAL neural networks, DEEP learning, MACHINE learning, FEATURE extraction, DIAGNOSIS

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

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

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

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

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

Autori: Cheng Yang Yannan Yuan Fu Wang a ďalší

Zdroj: Quality and Reliability Engineering International. 40:819-837

Predmety: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology, 7. Clean energy

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.

Autori: 马良玉 黄日灏 段晓冲 a ďalší

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.

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

Sparse deep encoded features with enhanced sinogramic red deer optimization for fault inspection in wafer maps.

Autori: Altantawy, Doaa A. Yakout, Mohamed A.

Zdroj: Journal of Intelligent Manufacturing. Jun2025, Vol. 36 Issue 5, p3359-3397. 39p.

Predmety: *MANUFACTURING processes, *INFORMATION processing, CONVOLUTIONAL neural networks, OPTIMIZATION algorithms, AUTOENCODERS

Sensor-Driven Surrogate Modeling and Control of Nonlinear Dynamical Systems Using FAE-CAE-LSTM and Deep Reinforcement Learning

Autori: Kherad, M. Moayyedi, M. K. Fotouhi-Ghazvini, F. a ďalší

Zdroj: Sensors. 25(16)

Predmety: Autoencoders, Control Of Dynamical Systems, Cyber-physical Systems, Deep Reinforcement Learning, Long Short-term Memory, Sensor-driven Modeling, Circular Cylinders, Computer Control Systems, Convolution, Dynamical Systems, Dynamics, Embedded Systems, Flow Control, Fuel Additives, Nonlinear Dynamical Systems, Real Time Control, Robust Control, Auto Encoders, Control Of Dynamical System, Cybe-physical Systems, High-dimensional, Higher-dimensional, Reinforcement Learning Agent, Reinforcement Learnings, Short Term Memory

Popis súboru: print

Prístupová URL adresa: https://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-73172
https://doi.org/10.3390/s25165149

Unsupervised sparse convolutional autoencoder for multi-class change detection in hyperspectral images

Autori: Bergamasco, Luca Bovolo, Francesca

Zdroj: Artificial Intelligence and Image and Signal Processing for Remote Sensing XXX. :22

Predmety: Convolutional Autoencoder, Hyperspectral images, Multi-class Change Detection, Spectral Unmixing, Unsupervised Change Detection

Convolutional autoencoder-based deep learning for intracerebral hemorrhage classification using brain CT images.

Autori: Nageswara Rao, B. Acharya, U. Rajendra Tan, Ru-San a ďalší

Zdroj: Cognitive Neurodynamics; 5/19/2025, Vol. 19 Issue 1, p1-13, 13p

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

Autori: Renato Melo Rafaelle Finotti António Guedes a ďalší

Zdroj: Applied Sciences, Vol 15, Iss 5, p 2662 (2025)

Predmety: structural health monitoring, railways, damage detection, out of roundness, sparse autoencoder, convolutional autoencoder, Technology, Engineering (General). Civil engineering (General), TA1-2040, Biology (General), QH301-705.5, Physics, QC1-999, Chemistry, QD1-999

Popis súboru: electronic resource

Relation: https://www.mdpi.com/2076-3417/15/5/2662; https://doaj.org/toc/2076-3417

Prístupová URL adresa: https://doaj.org/article/25623879dc094408963692cb2aa1b01c

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

Autori: Kalu, Kingsley Ataguba, Grace Onifade, Oyepeju a ďalší

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

Noise-Tolerant Data Reconstruction Based on Convolutional Autoencoder for Wireless Sensor Network †.

Autori: Lai, Trinh Thuc Tran, Tuan Phong Cho, Jaehyuk a ďalší

Zdroj: Applied Sciences (2076-3417); Sep2023, Vol. 13 Issue 18, p10090, 19p

Predmety: WIRELESS sensor networks, DATA recovery, NOISE, NOISE control

Enhanced heart sound anomaly detection via WCOS: a semi-supervised framework integrating wavelet, autoencoder and SVM.

Autori: Zeng, Peipei Kang, Shuimiao Fan, Fan a ďalší

Zdroj: Frontiers in Neuroinformatics; 2025, p1-15, 15p

Predmety: ANOMALY detection (Computer security), HEART murmurs, SUPPORT vector machines, CONGENITAL heart disease, AUTOENCODERS

Temperature scaling unmixing framework based on convolutional autoencoder

Autori: Jin Xu Mingming Xu Shanwei Liu a ďalší

Zdroj: International Journal of Applied Earth Observations and Geoinformation, Vol 129, Iss , Pp 103864- (2024)

Predmety: Hyperspectral unmixing, Convolutional autoencoder, Sparsity constraint, Temperature scaling, Equal-frequency binning, Physical geography, GB3-5030, Environmental sciences, GE1-350

Popis súboru: electronic resource

Relation: http://www.sciencedirect.com/science/article/pii/S1569843224002188; https://doaj.org/toc/1569-8432

Prístupová URL adresa: https://doaj.org/article/aa7533b7fbf447e1a8b51942e4c8c5f4

A Novel Multi-Task and Ensembled Optimized Parallel Convolutional Autoencoder and Transformer for Speech Emotion Recognition

Autori: Zahra Sharifzadeh Jafari Sanaz Seyedin

Zdroj: AUT Journal of Electrical Engineering, Vol 56, Iss 2, Pp 213-226 (2024)

Predmety: speech emotion recognition, mel frequency cepstral coefficients, autoencoder, transformer, multi-task deep learning, Electrical engineering. Electronics. Nuclear engineering, TK1-9971

Popis súboru: electronic resource

Relation: https://eej.aut.ac.ir/article_5336_945e73b38cfede1308072d0f634d7969.pdf; https://doaj.org/toc/2588-2910; https://doaj.org/toc/2588-2929

Prístupová URL adresa: https://doaj.org/article/09b910d7b3a44bcabfa7902391f7b0cb

A radar emitter structural identification method for complex conditions based on compressed sensing and an autoencoder.

Autori: Song, Yu Zhang, Wei Yang, Yaozu a ďalší

Zdroj: Nonlinear Dynamics; Aug2025, Vol. 113 Issue 15, p19159-19178, 20p

Electroencephalogram Emotion Recognition Based on 3D Feature Fusion and Convolutional Autoencoder.

Autori: An, Yanling Hu, Shaohai Duan, Xiaoying a ďalší

Zdroj: Frontiers in Computational Neuroscience; 10/18/2021, Vol. 15, p1-13, 13p

Predmety: EMOTION recognition, BRAIN-computer interfaces, SIGNAL convolution, DIFFERENTIAL entropy, CONVOLUTIONAL neural networks, ELECTROENCEPHALOGRAPHY, EMOTIONS, FEATURE extraction

Feature extraction of fields of fluid dynamics data using sparse convolutional autoencoder.

Autori: Obayashi, Wataru Aono, Hikaru Tatsukawa, Tomoaki a ďalší

Zdroj: AIP Advances; Oct2021, Vol. 11 Issue 10, p1-6, 6p

Predmety: FLUID dynamics, FEATURE extraction, PROPER orthogonal decomposition, NAVIER-Stokes equations, CONVOLUTIONAL neural networks, UNSTEADY flow, COMPRESSIBLE flow

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

Autori: Serag Mohamed Akila Elbrus Imanov Khaled Almezhghwi

Zdroj: Diagnostics, Vol 13, Iss 13, p 2199 (2023)

Predmety: chest pneumonia, classification, unsupervised learning, convolution, autoencoder, variational, Medicine (General), R5-920

Popis súboru: electronic resource

Relation: https://www.mdpi.com/2075-4418/13/13/2199; https://doaj.org/toc/2075-4418

Prístupová URL adresa: https://doaj.org/article/3f5772b5ed7f4a0e867c5884e5bbc516

A Particle Swarm Optimization-Based Flexible Convolutional Autoencoder for Image Classification.

Autori: Sun, Yanan Xue, Bing Zhang, Mengjie a ďalší

Zdroj: IEEE Transactions on Neural Networks & Learning Systems; Aug2019, Vol. 30 Issue 8, p2295-2309, 15p

Predmety: PARTICLE swarm optimization, CLASSIFICATION, COMPUTER architecture