Výsledky vyhledávání - "convolutional autoencoder(cae)"

River Channel Microgeomorphic Feature Extraction and Potential Sandstorm Source Identification Method Based on a Convolutional Autoencoder Model

Autoři: Kecong Wu Lirong Chen Yalige Bai a další

Zdroj: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 18, Pp 2602-2617 (2025)

Témata: convolutional autoencoder (CAE), Ocean engineering, QC801-809, Geophysics. Cosmic physics, microgeomorphic feature, Anomaly values, TC1501-1800, Yarlung Zangbo River, sandstorm sources

Přístupová URL adresa: https://doaj.org/article/94424c5cfbc34885963f0ffe4a93a78c

Unsupervised Feature Extraction From Raw Data for Gesture Recognition With Wearable Ultralow-Power Ultrasound

Autoři: Sergei Vostrikov Matteo Anderegg Luca Benini a další

Zdroj: IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control. 71:831-841

Témata: Male, Adult, Gestures, Signal Processing, Computer-Assisted, Hand, Armband, convolutional autoencoder (CAE), hand gesture recognition (HGR), wearable ultrasound (US), Pattern Recognition, Automated, Wearable Electronic Devices, Young Adult, Humans, Female, Algorithms, Ultrasonography, Unsupervised Machine Learning

Přístupová URL adresa: https://pubmed.ncbi.nlm.nih.gov/38787674

Multi-perspective Learning Based on Transformer for Stock Price Trend

Autoři: Xiliang Li Shuoru Chen Xiaoyan Qiao a další

Zdroj: International Journal of Computational Intelligence Systems, Vol 18, Iss 1, Pp 1-18 (2025)

Témata: Technical indicators, Multi-factor model, Transformer, Convolutional autoencoder (CAE), Stock trend prediction, Electronic computers. Computer science, QA75.5-76.95

Popis souboru: electronic resource

Relation: https://doaj.org/toc/1875-6883

Přístupová URL adresa: https://doaj.org/article/f4ccb21d10bc421492b489485a652be0

ECG Identification Algorithm Based on CAE and Improved VGGNet

Autoři: YAN Jie, ZHANG Yefei, ZHANG Xianfei

Zdroj: Jisuanji gongcheng, Vol 51, Iss 1, Pp 295-303 (2025)

Témata: electrocardiogram(ecg), ecg recognition, convolutional autoencoder(cae), residual network(resnet), signal preprocessing, Computer engineering. Computer hardware, TK7885-7895, Computer software, QA76.75-76.765

Popis souboru: electronic resource

Relation: https://www.ecice06.com/fileup/1000-3428/PDF/20250132.pdf; https://doaj.org/toc/1000-3428

Přístupová URL adresa: https://doaj.org/article/77f8130553644b1db92b5a3276a49a8b

A study on hybrid-architecture deep learning model for predicting pressure distribution in 2D airfoils

Autoři: Jaehyun Yoon Jaehyeok Doh

Zdroj: Scientific Reports, Vol 15, Iss 1, Pp 1-15 (2025)

Témata: Convolutional autoencoder (CAE), Convolutional neural networks (CNN), Fully-connected neural networks (FNN), Computational fluid dynamics (CFD), Medicine, Science

Popis souboru: electronic resource

Relation: https://doaj.org/toc/2045-2322

Přístupová URL adresa: https://doaj.org/article/c93aa0848de6482c9c0328655d316b71

Multiscale Hierarchical Losses to Preserve Hidden-Layer Features for Unsupervised Change Detection

Autoři: Bergamasco, Luca Bovolo, Francesca Bruzzone, Lorenzo

Přispěvatelé: Bergamasco, Luca Bovolo, Francesca Bruzzone, Lorenzo

Zdroj: IEEE Transactions on Geoscience and Remote Sensing. 62:1-16

Témata: Convolutional autoencoder (CAE), deep learning (DL), hierarchical loss function, multiresolution, multitemporal analysis, unsupervised change detection (CD), unsupervised learning

Popis souboru: application/pdf

Přístupová URL adresa: https://hdl.handle.net/11572/423695
https://ieeexplore.ieee.org/document/10623208
https://doi.org/10.1109/tgrs.2024.3438465

Robust sensor fault detection in wireless sensor networks using a hybrid conditional generative adversarial networks and convolutional autoencoder

Autoři: Khan, Rehan Saeed, Umer Koo, Insoo a další

Přispěvatelé: Khan, Rehan Saeed, Umer Koo, Insoo a další

Témata: Wireless Sensor Networks (WSNs), Convolutional Autoencoder (CAE), Gramian Angular Field (GAF), Conditional Generative Adversarial Networks (Conditional GANs), sensor faults, Subject Categories::G420 Networks and Communications

Relation: https://ieeexplore.ieee.org/document/10919044; http://hdl.handle.net/10547/626621; IEEE Sensors Journal

Dostupnost: http://hdl.handle.net/10547/626621
https://doi.org/10.1109/JSEN.2025.3547736

Surrogate Modeling of Hydrogen-Enriched Combustion Using Autoencoder-Based Dimensionality Reduction

Autoři: Lanfei Zhang Xu Chu Siyu Ding a další

Zdroj: Processes ; Volume 13 ; Issue 4 ; Pages: 1093

Témata: reduced order model (ROM), hydrogen-enriched combustion, convolutional autoencoder (CAE), fully connected autoencoder (FCAE), hyperparameter setting

Geografické téma: agris

Popis souboru: application/pdf

Relation: Process Control and Monitoring; https://dx.doi.org/10.3390/pr13041093

Dostupnost: https://doi.org/10.3390/pr13041093

Unsupervised Feature Extraction From Raw Data for Gesture Recognition With Wearable Ultralow-Power Ultrasound

Autoři: Vostrikov, Sergei Anderegg, Matteo Benini, Luca a další

Zdroj: IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control, 71 (7)

Témata: Armband, convolutional autoencoder (CAE), hand gesture recognition (HGR), wearable ultrasound (US)

Přístupová URL adresa: http://hdl.handle.net/20.500.11850/683989

Deep Learning Approach for Radar-Based People Counting

Autoři: Jae-Ho Choi Ji-Eun Kim Kyung-Tae Kim a další

Přispěvatelé: Jae-Ho Choi Ji-Eun Kim Kyung-Tae Kim a další

Zdroj: IEEE Internet of Things Journal. 9:7715-7730

Témata: CROWD, convolutional autoencoder (CAE), impulse radio ultra-wideband (IR-UWB) radar, radar-based people counting (RPC), Radar, Internet of Things, 02 engineering and technology, bidirectional recurrent neural network (Bi-RNN), TRACKING, Clutter, Deep learning (DL), 0202 electrical engineering, electronic engineering, information engineering, SMART CITIES, Feature extraction, Training, Radar clutter, Radar cross-sections

Přístupová URL adresa: https://ieeexplore.ieee.org/document/9540889

Ultrasonic Weld Quality Inspection Involving Strength Prediction and Defect Detection in Data-Constrained Training Environments

Autoři: Reenu Mohandas Patrick Mongan Martin Hayes a další

Přispěvatelé: Reenu Mohandas Patrick Mongan Martin Hayes a další

Zdroj: Sensors (Basel)
Sensors, Vol 24, Iss 20, p 6553 (2024)

Témata: convolutional autoencoder(CAE), autoencoder, convolutional autoencoder (CAE), Engineering, Chemical technology, Information and computing sciences, weld strength prediction, ultrasonic welding (USW), TP1-1185, Article, weld defect detection

Popis souboru: application/pdf

Přístupová URL adresa: https://pubmed.ncbi.nlm.nih.gov/39460042
https://doaj.org/article/c15dc7289fb44e848984d3241b20483a
https://hdl.handle.net/10344/14126
https://doi.org/10.34961/researchrepository-ul.27979589

Unsupervised Data Fusion With Deeper Perspective: A Novel Multisensor Deep Clustering Algorithm

Autoři: Kasra Rafiezadeh Shahi Pedram Ghamisi Behnood Rasti a další

Zdroj: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 15, Pp 284-296 (2022)

Témata: convolutional autoencoder (CAE), Ocean engineering, remote sensing, Autoencoder (AE), QC801-809, Geophysics. Cosmic physics, 0211 other engineering and technologies, deep learning, multisensor data fusion, 02 engineering and technology, 0101 mathematics, TC1501-1800, 01 natural sciences

Přístupová URL adresa: https://ieeexplore.ieee.org/ielx7/4609443/4609444/09638348.pdf
https://doaj.org/article/e78da2231b87497190e2ffcd669a023e

Ultrasonic weld quality inspection involving strength prediction and defect detection in data-constrained training environments

Autoři: Reenu Homandas Patrick Mongan Martin Hayes

Témata: Engineering, Information and computing sciences, weld strength prediction, autoencoder, weld defect detection, convolutional autoencoder(CAE), ultrasonic welding (USW)

Dostupnost: https://doi.org/10.34961/researchrepository-ul.27979589.v1
https://figshare.com/articles/journal_contribution/Ultrasonic_weld_quality_inspection_involving_strength_prediction_and_defect_detection_in_data-constrained_training_environments/27979589

Sky Image Prediction Model Based on Convolutional Auto-Encoder for Minutely Solar PV Power Forecasting

Autoři: Fu, Yuwei Chai, Hua Zhen, Zhao a další

Přispěvatelé: Fu, Yuwei Chai, Hua Zhen, Zhao a další

Zdroj: IEEE Transactions on Industry Applications. 57:3272-3281

Témata: ta222, 13. Climate action, solar PV power forecasting, sky image, 0202 electrical engineering, electronic engineering, information engineering, Convolutional autoencoder (CAE), minute time scale, fi=Sähkötekniikka|en=Electrical Engineering, 02 engineering and technology, spatiotemporal feature, 7. Clean energy

Popis souboru: fi=kokoteksti; en=fulltext; true

Přístupová URL adresa: http://juuli.fi/Record/0385226121
https://doi.org/10.1109/TIA.2021.3072025
https://ieeexplore.ieee.org/document/9399287/

Canopy Averaged Chlorophyll Content Prediction of Pear Trees Using Convolutional Autoencoder on Hyperspectral Data

Autoři: Subir Paul Vinayaraj Poliyapram Nevrez Imamoglu a další

Zdroj: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 13, Pp 1426-1437 (2020)

Témata: convolutional autoencoder (CAE), pear orchard, QC801-809, Geophysics. Cosmic physics, 0211 other engineering and technologies, deep learning, 04 agricultural and veterinary sciences, 02 engineering and technology, Canopy averaged chlorophyll content (CACC), Ocean engineering, hyperspectral (HS) data, 0401 agriculture, forestry, and fisheries, Gaussian process regression (GPR), TC1501-1800

Přístupová URL adresa: https://ieeexplore.ieee.org/ielx7/4609443/8994817/09050560.pdf
https://doaj.org/article/021ee32b52ce425c91b578ef0d36ccb1
https://ieeexplore.ieee.org/document/9050560/
https://ui.adsabs.harvard.edu/abs/2020IJSTA..13.1426P/abstract
http://eprints.iisc.ac.in/65531/
https://doi.org/10.1109/JSTARS.2020.2983000
https://dblp.uni-trier.de/db/journals/staeors/staeors13.html#PaulPIUNK20

RANet: Relationship Attention for Hyperspectral Anomaly Detection

Autoři: Yingzhao Shao Yunsong Li Li Li a další

Zdroj: Remote Sensing, Vol 15, Iss 23, p 5570 (2023)

Témata: anomaly detection, hyperspectral image, graph attention network (GAT), convolutional autoencoder (CAE), Science

Relation: https://www.mdpi.com/2072-4292/15/23/5570; https://doaj.org/toc/2072-4292; https://doaj.org/article/a6971d0c7fbd49b387ea1f8e7ba11002

Dostupnost: https://doi.org/10.3390/rs15235570
https://doaj.org/article/a6971d0c7fbd49b387ea1f8e7ba11002

DOA Estimation Based on Convolutional Autoencoder in the Presence of Array Imperfections

Autoři: Dah-Chung Chang Yan-Ting Liu

Zdroj: Electronics, Vol 12, Iss 3, p 771 (2023)

Témata: deep neural network, array imperfection, direction of arrival (DOA), autoencoder (AE), convolutional autoencoder (CAE), Electronics, TK7800-8360

Relation: https://www.mdpi.com/2079-9292/12/3/771; https://doaj.org/toc/2079-9292; https://doaj.org/article/3a534050891d4267a89745a21760832d

Dostupnost: https://doi.org/10.3390/electronics12030771
https://doaj.org/article/3a534050891d4267a89745a21760832d

Prediction of Contact Fatigue Performance Degradation Trends Based on Multi-Domain Features and Temporal Convolutional Networks

Autoři: Yu Liu Yuanbo Liu Yan Yang

Zdroj: Entropy, Vol 25, Iss 1316, p 1316 (2023)

Témata: contact fatigue, feature extraction, health indexes (HIs), degradation prediction, temporal convolutional network (TCN), convolutional autoencoder (CAE), Science, Astrophysics, QB460-466, Physics, QC1-999

Relation: https://www.mdpi.com/1099-4300/25/9/1316; https://doaj.org/toc/1099-4300; https://doaj.org/article/359040aff2754f5fb3b921e464c19403

Dostupnost: https://doi.org/10.3390/e25091316
https://doaj.org/article/359040aff2754f5fb3b921e464c19403

Quantification of respiratory effort magnitude in spontaneous breathing patients using Convolutional Autoencoders

Autoři: Ang, Christopher Yew Shuen Chiew, Yeong Shiong Vu, Lien Hong a další

Přispěvatelé: Ang, Christopher Yew Shuen Chiew, Yeong Shiong Vu, Lien Hong a další

Zdroj: Elements

Témata: Spontaneous breathing, Machine learning, Convolutional Autoencoder (CAE), Mechanical ventilation

Relation: https://scholarbank.nus.edu.sg/handle/10635/212801

Dostupnost: https://scholarbank.nus.edu.sg/handle/10635/212801

Non-Contact Detection of Delamination in Composite Laminates Coated with a Mechanoluminescent Sensor Using Convolutional AutoEncoder

Autoři: Seogu Park Jinwoo Song Heung Soo Kim a další

Zdroj: Mathematics ; Volume 10 ; Issue 22 ; Pages: 4254

Témata: composite materials, Convolutional AutoEncoder (CAE), delamination, mechanoluminescent (ML) sensor, non-contact sensing, structural health monitoring

Popis souboru: application/pdf

Relation: E: Applied Mathematics; https://dx.doi.org/10.3390/math10224254

Dostupnost: https://doi.org/10.3390/math10224254