Výsledky vyhledávání - "Autoencoder network"

A Novel PAPR Reduction Scheme Based on Deep Autoencoder Network for FBMC Systems

Autoři: Xing Cheng Deli Chen Shuaishuai Li a další

Zdroj: IEEE Access, Vol 13, Pp 68948-68958 (2025)

Témata: peak to average power ratio, denoising autoencoder network, deep learning, Filter bank multicarrier, Electrical engineering. Electronics. Nuclear engineering, TK1-9971

Přístupová URL adresa: https://doaj.org/article/678c4448230241fc87fe49f3e61edf69

VISTA: vision improvement via split and reconstruct deep neural network for fundus image quality assessment

Autoři: Saif Khalid Saddam Abdulwahab Oscar Agustín Stanchi a další

Zdroj: Neural Computing and Applications. 36:23149-23168

Témata: Autoencoder network, Fundus image, Interpretability, Explainability, Retinal image, Gradability, Quality assessment

Popis souboru: application/pdf

Přístupová URL adresa: http://hdl.handle.net/11336/247248

Enhanced water quality index prediction using a dual-key convolutional transformer autoencoder network integrating with poplar optimization

Autoři: R. Maruthamuthu S. Balamurugan N. Naveen Kumar a další

Zdroj: Franklin Open, Vol 13, Iss , Pp 100370- (2025)

Témata: Water quality index, Water quality class, Dual-key convolutional transformer autoencoder network, Poplar optimization algorithm, Technology

Popis souboru: electronic resource

Relation: http://www.sciencedirect.com/science/article/pii/S2773186325001586; https://doaj.org/toc/2773-1863

Přístupová URL adresa: https://doaj.org/article/bc6cba3cdab040f6a98286e4f3d6d2b8

Multi-Scale Contextual Coding for Human-Machine Vision of Volumetric Medical Images

Autoři: Jietao Chen Weijie Chen Qianjian Xing a další

Zdroj: IEEE Access, Vol 13, Pp 145663-145679 (2025)

Témata: Neural networks, volumetric medical image compression, human-machine vision, autoencoder network, entropy model, Electrical engineering. Electronics. Nuclear engineering, TK1-9971

Popis souboru: electronic resource

Relation: https://ieeexplore.ieee.org/document/11121294/; https://doaj.org/toc/2169-3536

Přístupová URL adresa: https://doaj.org/article/681d6b9d0f254827ab8b659bb836b448

Signal Enhancement for Downhole Microseismic Data Using Improved Attention Mechanism Based on Autoencoder Network

Autoři: Wenxuan Ge Qinghui Mao Wei Zhou a další

Zdroj: IEEE Access, Vol 12, Pp 156390-156400 (2024)

Témata: autoencoder network, first arrival picking, improved attention mechanism, Microseismic signal denoising, polarization analysis, Electrical engineering. Electronics. Nuclear engineering, TK1-9971

Přístupová URL adresa: https://doaj.org/article/2c58241bbbcf44c5824ba514c4ba0f3f

A Comparative Study of Sentiment-Aware Collaborative Filtering Algorithms for Arabic Recommendation Systems

Autoři: Sumaia Mohammed Al-Ghuribi Shahrul Azman Mohd Noah Mawal A. Mohammed a další

Zdroj: IEEE Access, Vol 12, Pp 174441-174454 (2024)

Témata: sentiment analysis, collaborative filtering, Arabic language, user reviews, Electrical engineering. Electronics. Nuclear engineering, deep autoencoder network, TK1-9971

Přístupová URL adresa: https://doaj.org/article/b6affff419e448dca46a96e202c36793

Mitigating the Concurrent Interference of Electrode Shift and Loosening in Myoelectric Pattern Recognition Using Siamese Autoencoder Network

Autoři: Ge Gao Xu Zhang Xiang Chen a další

Zdroj: IEEE Transactions on Neural Systems and Rehabilitation Engineering, Vol 32, Pp 3388-3398 (2024)

Témata: Male, Adult, Support Vector Machine, Gestures, Electromyography, electrode shift, electrode loosening, Reproducibility of Results, Siamese autoencoder network, RM1-950, surface electromyography, Pattern Recognition, Automated, Young Adult, Myoelectric pattern recognition, Medical technology, Humans, Female, Therapeutics. Pharmacology, Neural Networks, Computer, R855-855.5, Electrodes, Algorithms

Přístupová URL adresa: https://pubmed.ncbi.nlm.nih.gov/39196739
https://doaj.org/article/cc98e516e69945a6b12fa2043960d7c9

Real-Time Packet-Based Intrusion Detection on Edge Devices

Autoři: Niccolò Borgioli Linh Thi Xuan Phan Federico Aromolo a další

Zdroj: Proceedings of Cyber-Physical Systems and Internet of Things Week 2023. :234-240

Témata: anomaly detection, autoencoder, network traffic, real-time, unsupervised learning

Popis souboru: application/pdf

DAR-MDE: Depth-Attention Refinement for Multi-Scale Monocular Depth Estimation

Autoři: Saddam Abdulwahab Hatem A. Rashwan Moumen T. El-Melegy a další

Zdroj: Journal of Sensor and Actuator Networks, Vol 14, Iss 5, p 90 (2025)

Témata: accurate depth, depth attention, multi-scale aggregation, depth map estimation, autoencoder network, refining attention network, Technology

Popis souboru: electronic resource

Relation: https://www.mdpi.com/2224-2708/14/5/90; https://doaj.org/toc/2224-2708

Přístupová URL adresa: https://doaj.org/article/b5b4e060991a4e4e908724732eb7a0df

A Deep Learning-Based Method for Mechanical Equipment Unknown Fault Detection in the Industrial Internet of Things

Autoři: Xiaokai Liu Xiangheng Meng Lina Ning a další

Zdroj: Sensors, Vol 25, Iss 19, p 5984 (2025)

Témata: industrial internet of things, fault diagnosis, autoencoder network, convolutional neural network, long short-term memory network, Chemical technology, TP1-1185

Popis souboru: electronic resource

Relation: https://www.mdpi.com/1424-8220/25/19/5984; https://doaj.org/toc/1424-8220

Přístupová URL adresa: https://doaj.org/article/4e2448280e16462bbbbf1991b04c2d99

Network Anomaly Detection Integrating Dynamic Graph Embedding and Transformer Autoencoder

Autoři: ZHANG Anqin, DING Zhifeng

Zdroj: Jisuanji gongcheng, Vol 51, Iss 4, Pp 47-56 (2025)

Témata: dynamic graph embedding|transformer autoencoder|network anomaly detection|malicious behavior|long and short-term time-dependence, Computer engineering. Computer hardware, TK7885-7895, Computer software, QA76.75-76.765

Relation: https://www.ecice06.com/fileup/1000-3428/PDF/20250405.pdf; https://doaj.org/toc/1000-3428; https://doaj.org/article/a94a6f533a9c4c8fb8f5a8461c023e47

Dostupnost: https://doi.org/10.19678/j.issn.1000-3428.0070231
https://doaj.org/article/a94a6f533a9c4c8fb8f5a8461c023e47

Anomaly-Guided Double Autoencoders for Hyperspectral Unmixing

Autoři: Hongyi Liu Chenyang Zhang Jianing Huang a další

Zdroj: Remote Sensing ; Volume 17 ; Issue 5 ; Pages: 800

Témata: hyperspectral unmixing, autoencoder network, logarithm SAD, anomaly detection, attention module

Geografické téma: agris

Popis souboru: application/pdf

Relation: Remote Sensing Image Processing; https://dx.doi.org/10.3390/rs17050800

Dostupnost: https://doi.org/10.3390/rs17050800

Single-cell RNA-Seq Clustering Based on Dual Autoencoder with Variational Bayes

Autoři: JIA Jihua XU Yaokui WANG Minghui

Zdroj: Journal of Harbin University of Science and Technology, Vol 29, Iss 03, Pp 125-133 (2024)

Témata: single-cell rna sequencing, adversarial autoencoder, autoencoder network, variational bayes, cell clustering, Technology, Science

Popis souboru: electronic resource

Relation: https://hlgxb.hrbust.edu.cn/#/digest?ArticleID=2339; https://doaj.org/toc/1007-2683

Přístupová URL adresa: https://doaj.org/article/778a9e6dd5c34164acba336f3272be5a

Looseness Identification of Track Fasteners Based on Ultra-Weak FBG Sensing Technology and Convolutional Autoencoder Network

Autoři: Li, Sheng Jin, Liang Jiang, Jinpeng a další

Zdroj: Sensors. 22(15)

Témata: Data Management and Data Science, Civil Engineering, Information and Computing Sciences, Engineering, Clinical Research, Railroads, Technology, feature identification, track fastener looseness, distributed vibration, convolutional autoencoder network, pseudo-Hilbert scan, ultra-weak fiber optic Bragg grating, Analytical Chemistry, Environmental Science and Management, Ecology, Distributed Computing, Electrical and Electronic Engineering, Electrical engineering, Electronics, sensors and digital hardware, Environmental management, Distributed computing and systems software

Popis souboru: application/pdf

Přístupová URL adresa: https://escholarship.org/uc/item/4jq321md
https://escholarship.org/content/qt4jq321md/qt4jq321md.pdf

A graph autoencoder network to measure the geometric similarity of drainage networks in scaling transformation

Autoři: Huafei Yu Tinghua Ai Min Yang a další

Přispěvatelé: Huafei Yu Tinghua Ai Min Yang a další

Zdroj: International Journal of Digital Earth, Vol 16, Iss 1, Pp 1828-1852 (2023)

Témata: graph autoencoder network, drainage network, scaling transformation, Computer and Information Science, geometric similarity measurement, 0211 other engineering and technologies, Mathematical geography. Cartography, 02 engineering and technology, GA1-1776, 01 natural sciences, Geometric similarity measurement, Drainage network, 0105 earth and related environmental sciences

Popis souboru: application/pdf

Přístupová URL adresa: https://doaj.org/article/575a3cbef09a4a4fa6f260f437fe23be
https://hdl.handle.net/10356/173624

scBKAP: A Clustering Model for Single-Cell RNA-Seq Data Based on Bisecting K-Means

Autoři: Xiaolin Wang Hongli Gao Ren Qi a další

Přispěvatelé: Xiaolin Wang Hongli Gao Ren Qi a další

Zdroj: IEEE/ACM Transactions on Computational Biology and Bioinformatics. 20:2007-2015

Témata: autoencoder network, 0301 basic medicine, 0303 health sciences, ScRNA-seq, Sequence Analysis, RNA, Gene Expression Profiling, bisecting K-means clustering, Single-Cell Gene Expression Analysis, 03 medical and health sciences, Cluster Analysis, MPDR dimensionality reduction, Single-Cell Analysis, Algorithms

Popis souboru: application/pdf

Přístupová URL adresa: https://pubmed.ncbi.nlm.nih.gov/37015596

Enhanced Prediction of the Remaining Useful Life of Rolling Bearings Under Cross-Working Conditions via an Initial Degradation Detection-Enabled Joint Transfer Metric Network

Autoři: Lingfeng Qi Jiafang Pan Tianping Huang a další

Zdroj: Applied Sciences, Vol 15, Iss 12, p 6401 (2025)

Témata: remaining useful life prediction, reconstruction along projection pathway, deep adversarial convolution autoencoder network, joint domain adaptation loss, 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/2076-3417/15/12/6401; https://doaj.org/toc/2076-3417

Přístupová URL adresa: https://doaj.org/article/e5b80ed94f004b17a3ca4adee50fd0fc

Brain fingerprinting and cognitive behavior predicting using functional connectome of high inter-subject variability

Autoři: Jiayu Lu Tianyi Yan Lan Yang a další

Zdroj: NeuroImage, Vol 295, Iss , Pp 120651- (2024)

Témata: Conditional variational autoencoder network, Fingerprint, Functional connectivity, Individual identification, Cognitive behavior predicting, Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571

Popis souboru: electronic resource

Relation: http://www.sciencedirect.com/science/article/pii/S1053811924001460; https://doaj.org/toc/1095-9572

Přístupová URL adresa: https://doaj.org/article/b5fa488487ef4ae393a70d363554f0d8

Detecting Changes by Learning No Changes: Data-Enclosing-Ball Minimizing Autoencoders for One-Class Change Detection in Multispectral Imagery

Autoři: Lichao Mou Yuansheng Hua Sudipan Saha a další

Přispěvatelé: Lichao Mou Yuansheng Hua Sudipan Saha a další

Zdroj: IEEE Transactions on Geoscience and Remote Sensing. 60:1-16

Témata: remote sensing, Autoencoder network, change detection, one-class classification, 0211 other engineering and technologies, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology, ddc

Popis souboru: application/pdf; STAMPA

Přístupová URL adresa: https://ieeexplore.ieee.org/document/9870684/authors
https://doi.org/10.1109/TGRS.2022.3200985
https://hdl.handle.net/11572/354885
https://mediatum.ub.tum.de/1772148

Electricity Behavior Modeling and Anomaly Detection Services Based on a Deep Variational Autoencoder Network

Autoři: Rongheng Lin Shuo Chen Zheyu He a další

Zdroj: Energies, Vol 17, Iss 16, p 3904 (2024)

Témata: load pattern, anomaly detection, autoencoder network, Technology

Relation: https://www.mdpi.com/1996-1073/17/16/3904; https://doaj.org/toc/1996-1073; https://doaj.org/article/7911e43c076340d9899c9bc1aa6ea9af

Dostupnost: https://doi.org/10.3390/en17163904
https://doaj.org/article/7911e43c076340d9899c9bc1aa6ea9af