Výsledky vyhledávání - deep convolutional autoencoder

Latent Space Classification for Cardiovascular Disease Detection: A Deep Convolutional Autoencoder-Based Approach for Telemedicine Applications

Autoři: G Antoni Gracy Sheena Christabel Pravin

Zdroj: IEEE Access, Vol 13, Pp 129195-129212 (2025)

Témata: MIT-BIH arrhythmia database, deep convolutional autoencoders, telemedicine, Electrical engineering. Electronics. Nuclear engineering, Cardio-vascular diseases, energy efficiency, latent space classification system, TK1-9971

Přístupová URL adresa: https://doaj.org/article/673f3d321fcf4c7db059c82fb5f3960a

Unsupervised Induction Motor Anomaly Detection Using a Deep Convolutional Autoencoder Based on Multi-Sensor Data Fusion

Autoři: Andrea Visentin Marco Dalla Benjamin Provan-Bessell a další

Zdroj: 2025 IEEE International Conference on Smart Computing (SMARTCOMP). :194-201

Superficial Maxillofacial Venous Imaging Enhancement Using a Deep Convolutional Autoencoder with Wavelet Downsampling

Autoři: Zengkai Li Jiuai Sun Chaoli Wang a další

Zdroj: 2025 2nd International Conference on Electronic Engineering and Information Systems (EEISS). :1-5

Automated Anomaly Detection and Classification in Crystal Lattice Defect Mapping via Deep Convolutional Autoencoder-Enhanced Feature Extraction and HyperScore-Based Prioritization

Autoři: Freederia AI Researcher

Integrating multi-source monitoring data and deep convolutional autoencoder technology for slope failure pattern recognition

Autoři: Nana Han Wending Miao Mingzhi Li a další

Zdroj: Frontiers in Earth Science, Vol 13 (2025)

Témata: health monitoring, Science, rainfall, slope displacement, multi-source data fusion, deep convolutional autoencoder

Přístupová URL adresa: https://doaj.org/article/4440996c733b4eaf8040edb8e0c3f0dd

A Deep Convolutional Autoencoder with Metaheuristic Optimization based Feature Reduction Framework for Genetic Disorder Detection Model

Zdroj: Journal of Intelligent Systems and Internet of Things. 18

Automatic Baseline Correction of 1D Signals Using a Parameter-Free Deep Convolutional Autoencoder Algorithm

Autoři: Łukasz Górski Małgorzata Jakubowska

Zdroj: Applied Sciences, Vol 15, Iss 22, p 12069 (2025)

Témata: baseline correction, deep neural networks, convolutional autoencoder, voltammetry, 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/2076-3417/15/22/12069; https://doaj.org/toc/2076-3417

Přístupová URL adresa: https://doaj.org/article/e5f44f18c48948af8ddb6d7b35698b37

Broadband Communication Signal Detection Using Deep Convolutional Autoencoder and Spectrum Center Network

Autoři: Bin Wei

Zdroj: Informatica. 49

Bleaching Detection in Coral Reef using Deep Convolutional Autoencoder based Model

Autoři: Neeraj Kumar Gautam Mayank Mishra Umesh C. Pati

Zdroj: 2024 4th International Conference on Artificial Intelligence and Signal Processing (AISP). :01-05

Efficient Bayesian full-waveform inversion using a deep convolutional autoencoder prior

Autoři: Shuhua Hu Mrinal K Sen Zeyu Zhao a další

Zdroj: Fourth International Meeting for Applied Geoscience & Energy. :993-997

A deep convolutional autoencoder to predict the position of the full-body centre of mass from lower limb kinematics

Autoři: Maxime Devanne Morgan Sangeux

Zdroj: Gait & Posture. 121:61-62

Towards Automated EEG-Based Detection Using Deep Convolutional Autoencoders

Autoři: Stiehl, Annika Weeger, Nicolas Uhl, Christian a další

Témata: Signal Processing (eess.SP), Signal Processing, FOS: Electrical engineering, electronic engineering, information engineering

Přístupová URL adresa: http://arxiv.org/abs/2508.20535

Driver Distraction Classification Using Deep Convolutional Autoencoder and Ensemble Learning

Autoři: Anirudh Muthuswamy M. Ali Akber Dewan Mahbub Murshed a další

Zdroj: IEEE Access, Vol 11, Pp 71435-71448 (2023)

Témata: driver distraction, autoencoders, dynamic ensemble classification, CNNs, Deep learning, Electrical engineering. Electronics. Nuclear engineering, TK1-9971

Přístupová URL adresa: https://doaj.org/article/864f5caf02254dc485057c4ac9e7914d

Deep convolutional autoencoder thermography for artwork defect detection

Autoři: Yi Liu Fumin Wang Kaixin Liu a další

Zdroj: Quantitative InfraRed Thermography Journal. 21:367-383

Témata: Non-destructive testing, infrared thermography, autoencoder, noise reduction, artwork

DOA estimation method for sparse arrays based on deep convolutional autoencoder and deep convolutional neural network

Autoři: Shuhan Guo Qin Zhang Xiaolong Fu a další

Zdroj: Digital Signal Processing. 168:105627

Interference Suppression for an FM-Radio-Based Passive Radar via Deep Convolutional Autoencoder

Autoři: Do-Hyun Park Geun-Ho Park Ji-Hun Park a další

Zdroj: IEEE Transactions on Aerospace and Electronic Systems. 60:106-118

Témata: 0203 mechanical engineering, 0211 other engineering and technologies, 02 engineering and technology

Mine Microseismic Signal Denoising Based on a Deep Convolutional Autoencoder

Autoři: Ting Hu Bin Xu Yongfa Wang a další

Zdroj: Shock and Vibration, Vol 2023 (2023)

Témata: Physics, QC1-999, 0211 other engineering and technologies, 02 engineering and technology, 01 natural sciences, 0105 earth and related environmental sciences

Popis souboru: text/xhtml

Přístupová URL adresa: https://doaj.org/article/d211f2fa16324c2f8f5ddc71c917d688

Deep Convolutional Autoencoder Applied for Noise Reduction in Range-Doppler Maps of FMCW Radars

Autoři: Marcio L. Lima de Oliveira Marco J. G. Bekooij

Zdroj: 2020 IEEE International Radar Conference (RADAR). :630-635

Témata: Deep Learning, Radar, 22/2 OA procedure, 0202 electrical engineering, electronic engineering, information engineering, Autoencoder, Convolutional, 02 engineering and technology, Doppler-Range

Přístupová URL adresa: https://www.narcis.nl/publication/RecordID/oai%3Aris.utwente.nl%3Apublications%2F9e7272ea-6d04-49d1-88c5-aef9b05c56b4
https://utwente-staging.elsevierpure.com/en/publications/deep-convolutional-autoencoder-applied-for-noise-reduction-in-ran
https://ieeexplore.ieee.org/document/9114719/
https://research.utwente.nl/en/publications/deep-convolutional-autoencoder-applied-for-noise-reduction-in-ran

Drone Ego-Noise Cancellation for Improved Speech Capture using Deep Convolutional Autoencoder Assisted Multistage Beamforming

Autoři: Song, Yanjue Kindt, Stijn Madhu, Nilesh

Zdroj: 2022 25th International Conference on Information Fusion (FUSION)

Témata: Technology and Engineering, UNet, 02 engineering and technology, Drone, ego-noise reduction, REDUCTION, ENHANCEMENT, unmanned aerial vehicle (UAV), autoencoders, MVDR, MWF, 0202 electrical engineering, electronic engineering, information engineering, beamformer, speech enhancement

Popis souboru: application/pdf

Přístupová URL adresa: https://biblio.ugent.be/publication/8767408/file/8767411
http://hdl.handle.net/1854/LU-8767408
http://doi.org/10.23919/fusion49751.2022.9841383
https://biblio.ugent.be/publication/8767408

Spatiotemporal Image-Based Flight Trajectory Clustering Model with Deep Convolutional Autoencoder Network

Autoři: Ye Liu Kam K. H. Ng Nana Chu a další

Zdroj: Journal of Aerospace Information Systems. 20:575-587

Témata: 0502 economics and business, 05 social sciences, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology