Search Results - deep autoencoder network

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

Authors: Xing Cheng Deli Chen Shuaishuai Li et al.

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

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

Access URL: https://doaj.org/article/678c4448230241fc87fe49f3e61edf69

Enhanced Short-Term GHI Prediction using Cloud-Aware Deep Autoencoder Network

Authors: Kalpalathika N Jumin Salih Lakshmi P et al.

Source: 2025 5th International Conference on Soft Computing for Security Applications (ICSCSA). :890-896

Proximal Mapping-Incorporated Deep Autoencoder Network with Momentum Acceleration Method for Image Denoising

Authors: Yang Zhao Ming Li Meng Huang et al.

Source: 2025 IEEE 14th Data Driven Control and Learning Systems (DDCLS). :1322-1327

NCAE: data-driven representations using a deep network-coherent DNA methylation autoencoder identify robust disease and risk factor signatures

Authors: Martinez-Enguita, David Dwivedi, Sanjiv K. Jörnsten, Rebecka et al.

Source: Briefings in Bioinformatics. 24(5)

Subject Terms: DNA methylation, deep learning, autoencoders, biomarkers, systems medicine, transfer learning

File Description: electronic

Access URL: https://research.chalmers.se/publication/537413
https://research.chalmers.se/publication/537413/file/537413_Fulltext.pdf

Elephant Flows Detection Using Deep Neural Network, Convolutional Neural Network, Long Short-Term Memory, and Autoencoder

Authors: Geremew, Getahun Wassie Ding, Jianguo

Source: Journal of Computer Networks and Communications. 2023

File Description: electronic

Access URL: https://urn.kb.se/resolve?urn=urn:nbn:se:bth-25213
https://doi.org/10.1155/2023/1495642

Deep-Feature-Based Autoencoder Network for Few-Shot Malicious Traffic Detection

Authors: He, Mingshu Wang, Xiaojuan Zhou, Junhua et al.

Source: Security and Communication Networks. 2021

File Description: print

Access URL: https://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-294023
https://doi.org/10.1155/2021/6659022

A health indicator construction method of rolling bearing based on vibration image features and deep autoencoder network

Authors: Yong Duan Xiangang Cao Jiangbin Zhao et al.

Source: 2023 5th International Conference on System Reliability and Safety Engineering (SRSE). :268-273

A Novel Lane-Changing Decision Model for Autonomous Vehicles Based on Deep Autoencoder Network and XGBoost

Authors: Xinping Gu Yunpeng Han Junfu Yu

Source: IEEE Access, Vol 8, Pp 9846-9863 (2020)

Subject Terms: Autonomous vehicle, 0502 economics and business, 05 social sciences, Electrical engineering. Electronics. Nuclear engineering, deep autoencoder network, lane-changing identification, lane-changing decision-making, XGBoost, TK1-9971

Access URL: https://ieeexplore.ieee.org/ielx7/6287639/8948470/08950329.pdf
https://doaj.org/article/67071ac15d7c48968c49a9255c43bf9e
https://dblp.uni-trier.de/db/journals/access/access8.html#GuHY20
https://ieeexplore.ieee.org/document/8950329/

Hybrid deep autoencoder network based adaptive cross guided bilateral filter for motion artifacts correction and denoising from MRI

Authors: Shiju Samuel Rohini S. Ochawar M.S.S. Rukmini

Source: The Imaging Science Journal. 72:76-91

DAEN: Deep Autoencoder Networks for Hyperspectral Unmixing

Authors: Yuanchao Su Jun Li Antonio Plaza et al.

Contributors: Yuanchao Su Jun Li Antonio Plaza et al.

Source: IEEE Transactions on Geoscience and Remote Sensing. 57:4309-4321

Subject Terms: Deep autoencoder network (DAEN), endmember identification, hyperspectral unmixing, 0211 other engineering and technologies, 0202 electrical engineering, electronic engineering, information engineering, deep learning, variational autoencoder (VAE), 02 engineering and technology

File Description: STAMPA

Access URL: https://ieeexplore.ieee.org/document/8628241
https://doi.org/10.1109/TGRS.2018.2890633
https://dblp.uni-trier.de/db/journals/tgrs/tgrs57.html#SuLPMGC19
https://ui.adsabs.harvard.edu/abs/2019ITGRS..57.4309S/abstract

Dual Deep Autoencoder Split Generative Adversarial Networks with Gooseneck Barnacle Optimization-Based Prediction of Autism Spectrum Disorder in Facial Images.

Authors: Goddu, Jyothi Anuradha, S. Srinivas, Yarramalle

Source: International Journal of Computational Intelligence & Applications. Jun2025, Vol. 24 Issue 2, p1-40. 40p.

Subject Terms: GENERATIVE adversarial networks, AUTISM spectrum disorders, AUTOENCODERS, DEVELOPMENTAL disabilities, RESEARCH personnel

Research on a Feature Enhancement Extraction Method for Underwater Targets Based on Deep Autoencoder Networks

Authors: Fang Ji Guonan Li Shaoqing Lu et al.

Source: Applied Sciences, Vol 14, Iss 4, p 1341 (2024)

Subject Terms: large underwater vehicles, deep autoencoder network, very low signal-to-noise ratio, line spectrum enhancement, Technology, Engineering (General). Civil engineering (General), TA1-2040, Biology (General), QH301-705.5, Physics, QC1-999, Chemistry, QD1-999

File Description: electronic resource

Relation: https://www.mdpi.com/2076-3417/14/4/1341; https://doaj.org/toc/2076-3417

Access URL: https://doaj.org/article/2f5ecb6bba1b4f8abaefd7de080c6198

Quality of Service-Aware Resource Selection in Healthcare IoT Using Deep Autoencoder Neural Networks

Authors: Manikandan, Ramachandran Indu de Albuquerque, Victor Hugo C. et al.

Source: Human-centric Computing and Information Sciences. 12(36):1-16

Subject Terms: D2d, Healthcare, Hetnet, Iot, Qos, Spectrum reuse

File Description: print

Access URL: https://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-48908

A Combination of Deep Autoencoder and Multi-Scale Residual Network for Landslide Susceptibility Evaluation

Authors: Zhuolu Wang Shenghua Xu Jiping Liu et al.

Source: Remote Sensing, Vol 15, Iss 3, p 653 (2023)

Subject Terms: landslide susceptibility, deep autoencoder, convolutional neural networks, residual learning, multiscale, Science

File Description: electronic resource

Relation: https://www.mdpi.com/2072-4292/15/3/653; https://doaj.org/toc/2072-4292

Access URL: https://doaj.org/article/09b03fdab1c34e289a7ad16b501d718a

Social movie recommender system based on deep autoencoder network using Twitter data

Authors: Hossein Tahmasebi Reza Ravanmehr Rezvan Mohamadrezaei

Source: Neural Computing and Applications. 33:1607-1623

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

Access URL: https://link.springer.com/article/10.1007/s00521-020-05085-1
https://dblp.uni-trier.de/db/journals/nca/nca33.html#TahmasebiRM21
https://doi.org/10.1007/s00521-020-05085-1

A Design of Intrusion Detection using Modified Bat Algorithm and Deep Autoencoder Network

Authors: Soundari D.V M.E. Kuralarasi R Kalieshwari S et al.

Source: International Journal of Innovative Technology and Exploring Engineering. 9:571-576

Investigating the Effects of Spanwise Transversal Traveling Waves on a Turbulent Compressible Flat Plate Flow With the Aid of a Deep Autoencoder Network

Authors: Shao, Xiao Ayan, Hilmi Oguzhan Hübenthal, Fabian et al.

Source: Jülich : Forschungszentrum Jülich GmbH Zentralbibliothek, Verlag, Schriften des Forschungszentrums Jülich IAS Series 69, 89-93 (2025). doi:10.34734/FZJ-2025-02462 ; Proceedings of the 35th Parallel CFD International Conference 2024 ; Proceedings of the 35th Parallel CFD International Conference 2024 35th Parallel CFD International Conference 2024, ParCFD 2024, Bonn, Germany, 2024-09-02 - 2024-09-04

Subject Geographic: DE

Relation: info:eu-repo/grantAgreement/EC//951733

Availability: https://juser.fz-juelich.de/record/1041830
https://juser.fz-juelich.de/search?p=id:%22FZJ-2025-02462%22

Direction of Arrival Estimation by Using Deep Autoencoder Network

Authors: Ekin Nurbas Emrah Onat

Source: 2020 28th Signal Processing and Communications Applications Conference (SIU). :1-4

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

Access URL: http://xplorestaging.ieee.org/ielx7/9302025/9302026/09302422.pdf?arnumber=9302422

A deep autoencoder network connected to geographical random forest for spatially aware geochemical anomaly detection

Authors: Zeinab Soltani Hossein Hassani Saeid Esmaeiloghli

Source: Computers & Geosciences. 190:105657

Nonlinear Unmixing of Hyperspectral Data via Deep Autoencoder Networks

Authors: Mou Wang Min Zhao Jie Chen et al.

Source: IEEE Geoscience and Remote Sensing Letters. 16:1467-1471

Subject Terms: 0211 other engineering and technologies, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Access URL: https://ieeexplore.ieee.org/document/8667664
https://dblp.uni-trier.de/db/journals/lgrs/lgrs16.html#WangZCR19
https://ui.adsabs.harvard.edu/abs/2019IGRSL..16.1467W/abstract