Suchergebnisse - robust convolutional autoencoder~

Hybrid Attention-Enhanced Regularized Convolutional Autoencoder for Robust EEG Feature Extraction in Seizure Prediction

Autoren: Yu-Hao Chen Hsiang-Yu Chen Yu-Chia Chen et al.

Quelle: IEEE Access, Vol 13, Pp 161053-161072 (2025)

Schlagwörter: Seizure prediction, feature extraction, convolutional autoencoder, hybrid attention, regularization, Electrical engineering. Electronics. Nuclear engineering, TK1-9971

Dateibeschreibung: electronic resource

Relation: https://ieeexplore.ieee.org/document/11155096/; https://doaj.org/toc/2169-3536

Zugangs-URL: https://doaj.org/article/966fe6d7c0a14654a1af2c536e46af53

Convolutional Autoencoder With Sequential and Channel Attention for Robust ECG Signal Denoising With Edge Device Implementation

Autoren: Alif Wicaksana Ramadhan Syifa Kushirayati Salsabila Aurellia et al.

Quelle: IEEE Access, Vol 13, Pp 54407-54422 (2025)

Schlagwörter: Autoencoder, convolutional neural networks (CNN), ECG, signal denoising, LSTM, Electrical engineering. Electronics. Nuclear engineering, TK1-9971

Dateibeschreibung: electronic resource

Relation: https://ieeexplore.ieee.org/document/10925413/; https://doaj.org/toc/2169-3536

Zugangs-URL: https://doaj.org/article/6dac22e57f934cb1b8bc12995f41ee58

Hybrid robust convolutional autoencoder for unsupervised anomaly detection of machine tools under noises

Autoren: Yan, Shen Shao, Haidong Xiao, Yiming et al.

Quelle: Robotics and Computer-Integrated Manufacturing. 79

Schlagwörter: Machine tools, Deep learning, Unsupervised anomaly detection, Hybrid robust convolutional autoencoder, Noises, Drift och underhållsteknik, Operation and Maintenance

Dateibeschreibung: print

Zugangs-URL: https://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-92934

Multi-loss Function in Robust Convolutional Autoencoder for Reconstruction Low-quality Fingerprint Image

Autoren: Farchan Hakim Raswa Franki Halberd Agus Harjoko et al.

Quelle: 2022 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC). :428-431

Schlagwörter: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Robust deep image clustering using convolutional autoencoder with separable discrete Krawtchouk and Hahn orthogonal moments

Autoren: Aymane Bouali Ilham El Ouariachi Azeddine Zahi et al.

Quelle: Intelligent Systems with Applications, Vol 22, Iss , Pp 200387- (2024)

Schlagwörter: Deep clustering, Autoencoder, Discrete separable orthogonal moments, Hahn moments, Krawtchouk moments, Image clustering, Cybernetics, Q300-390, Electronic computers. Computer science, QA75.5-76.95

Dateibeschreibung: electronic resource

Relation: http://www.sciencedirect.com/science/article/pii/S2667305324000620; https://doaj.org/toc/2667-3053

Zugangs-URL: https://doaj.org/article/595d93787957438994da59abb3bd4045

A gated temporal attention based intra prediction framework for robust deepfake video detection

Autoren: J. Eric Clapten v. Balaji

Quelle: Scientific Reports, Vol 15, Iss 1, Pp 1-28 (2025)

Schlagwörter: Deepfake detection, Video processing, Deep learning, Intra prediction, Gated temporal attention, Convolutional autoencoder, Medicine, Science

Dateibeschreibung: electronic resource

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

Zugangs-URL: https://doaj.org/article/f238bc65ca794bbba11737abe2bb2d6a

A performance analysis of convolutional autoencoder modified WaveGAN architectures for realistic 12 lead electrocardiogram synthesis

Autoren: Jiaqi Liu Kwok Tai Chui Lap-Kei Lee et al.

Quelle: Scientific Reports, Vol 15, Iss 1, Pp 1-22 (2025)

Schlagwörter: 12-Lead ECG synthesis, Convolutional autoencoder, Deep learning, ECG data generation, Feature extraction, Generative adversarial networks, Medicine, Science

Dateibeschreibung: electronic resource

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

Zugangs-URL: https://doaj.org/article/dec4e72d30e840b98711653b47323356

DHCAE: Deep Hybrid Convolutional Autoencoder Approach for Robust Supervised Hyperspectral Unmixing

Autoren: Fazal Hadi Jingxiang Yang Matee Ullah et al.

Quelle: Remote Sensing, Vol 14, Iss 18, p 4433 (2022)

Schlagwörter: hyperspectral unmixing (HSU), hybrid 3D, 2D-convolutional autoencoder (AE) network, supervised, spectral–spatial, remote sensing, Science

Dateibeschreibung: electronic resource

Relation: https://www.mdpi.com/2072-4292/14/18/4433; https://doaj.org/toc/2072-4292

Zugangs-URL: https://doaj.org/article/69fbfd032a87448097b06b1e155cb7e2

Data-driven non-intrusive reduced order modelling of selective laser melting additive manufacturing process using proper orthogonal decomposition and convolutional autoencoder

Autoren: Shubham Chaudhry Azzedine Abdedou Azzeddine Soulaïmani

Quelle: Advanced Modeling and Simulation in Engineering Sciences, Vol 12, Iss 1, Pp 1-23 (2025)

Schlagwörter: Reduced-order model, Convolutional autoencoder, Additive manufacturing, Deep learning, Proper orthogonal decomposition, Mechanics of engineering. Applied mechanics, TA349-359, Systems engineering, TA168

Dateibeschreibung: electronic resource

Relation: https://doaj.org/toc/2213-7467

Zugangs-URL: https://doaj.org/article/1acb9d02b46540cbb5ab687871ded7c0

Harnessing Large-Scale University Registrar Data for Predictive Insights: A Data-Driven Approach to Forecasting Undergraduate Student Success with Convolutional Autoencoders

Autoren: Mohammad Erfan Shoorangiz Michal Brylinski

Quelle: Machine Learning and Knowledge Extraction, Vol 7, Iss 3, p 80 (2025)

Schlagwörter: predictive modeling, student success, graduation prediction, convolutional autoencoder, machine learning in education, dimensionality reduction, Computer engineering. Computer hardware, TK7885-7895

Dateibeschreibung: electronic resource

Relation: https://www.mdpi.com/2504-4990/7/3/80; https://doaj.org/toc/2504-4990

Zugangs-URL: https://doaj.org/article/a0896dacf7b74fdb8a04329b58f288b7

Weighted salp swarm algorithm with deep learning-powered cyber-threat detection for robust network security

Autoren: Maha M. Althobaiti José Escorcia-Gutierrez

Quelle: AIMS Mathematics, Vol 9, Iss 7, Pp 17676-17695 (2024)

Schlagwörter: cyber threat, intrusion detection systems, salp swarm algorithm, network security, convolutional autoencoder, Mathematics, QA1-939

Dateibeschreibung: electronic resource

Relation: https://doaj.org/toc/2473-6988

Zugangs-URL: https://doaj.org/article/70ff11a1d438471ba0570f1e62c30cef

Artifact detection in fluorescence microscopy using convolutional autoencoder

Autoren: Fabian Rehn Marlene Pils Tuyen Bujnicki et al.

Quelle: Scientific Reports, Vol 15, Iss 1, Pp 1-12 (2025)

Schlagwörter: Medicine, Science

Dateibeschreibung: electronic resource

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

Zugangs-URL: https://doaj.org/article/27404f7d82f1406facf1fbc4adfaf845

Optimized Temporal Denoised Convolutional Autoencoder for Enhanced ADHD Classification Using fMRI Data

Autoren: Zarina Begum Kareemulla Shaik

Quelle: IEEE Access, Vol 13, Pp 29031-29045 (2025)

Schlagwörter: Attention deficit hyperactivity disorder, fMRI images, spatial features, optimized temporal denoised convolutional autoencoder, adaptive osprey optimization, deep learning, Electrical engineering. Electronics. Nuclear engineering, TK1-9971

Dateibeschreibung: electronic resource

Relation: https://ieeexplore.ieee.org/document/10877836/; https://doaj.org/toc/2169-3536

Zugangs-URL: https://doaj.org/article/a8ff8ca9acda4137b99f9fee50cebd36

Computationally Efficient Hyperspectral Image Classification Using Deep Autoencoder and Multistage 2 Dimensional Convolutional Autoencoder Architectures.

Autoren: Burnase, Sneha R. Sonar, Poonam N. Shelare, Maitreya

Quelle: Procedia Computer Science. 2025, Vol. 260, p1017-1025. 9p.

Schlagwörter: Image recognition (Computer vision), Autoencoder, Time complexity, Support vector machines, Feature extraction

Secret Key Generation Driven by Attention-Based Convolutional Autoencoder and Quantile Quantization for IoT Security in 5G and Beyond

Autoren: Anas Alashqar Ehsan Olyaei Torshizi Raed Mesleh et al.

Quelle: IEEE Access, Vol 13, Pp 131744-131756 (2025)

Schlagwörter: Autoencoder, self-attention, CNN, deep learning, IoT security, channel reciprocity, Electrical engineering. Electronics. Nuclear engineering, TK1-9971

Dateibeschreibung: electronic resource

Relation: https://ieeexplore.ieee.org/document/11086605/; https://doaj.org/toc/2169-3536

Zugangs-URL: https://doaj.org/article/0b76fcf31d6f473b829a5031cea1e7e5

CAECC-Subtyper: A Novel Convolutional Autoencoder Framework for Integrating Multi-omics Data in Cancer Subtyping.

Autoren: Uyar H Gumus O

Quelle: Biochemical genetics [Biochem Genet] 2025 Dec 04. Date of Electronic Publication: 2025 Dec 04.

Publikationsart: Journal Article

Info zur Zeitschrift: Publisher: Kluwer Academic/Plenum Publishers Country of Publication: United States NLM ID: 0126611 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1573-4927 (Electronic) Linking ISSN: 00062928 NLM ISO Abbreviation: Biochem Genet Subsets: MEDLINE

Graph-informed convolutional autoencoder to classify brain responses during sleep

Autoren: Sahar Zakeri Somayeh Makouei Sebelan Danishvar

Quelle: Frontiers in Neuroscience, Vol 19 (2025)

Schlagwörter: auditory stimuli, convolutional neural network, EEG, functional connectivity, graphical representation, sleep, Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571

Dateibeschreibung: electronic resource

Relation: https://www.frontiersin.org/articles/10.3389/fnins.2025.1525417/full; https://doaj.org/toc/1662-453X

Zugangs-URL: https://doaj.org/article/a03711a5ed214646aa5c2d62ac7f7aca

Development of game theoretic hypergraph based autoencoder scheme for multiple objects tracking and anomaly detection for surveillance videos

Autoren: Palanivel Srinivasan Karthik Mohan Manivannan Doraipandian et al.

Quelle: Scientific Reports, Vol 15, Iss 1, Pp 1-11 (2025)

Schlagwörter: Hypergraph, Game-theory, Video anomaly detection, Robust features, Autoencoder, Medicine, Science

Dateibeschreibung: electronic resource

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

Zugangs-URL: https://doaj.org/article/8c294c30278244d6ba63c3eb71ff0c60

Multivariate Physics-Informed Convolutional Autoencoder for Anomaly Detection in Power Distribution Systems with High Penetration of DERs

Autoren: Zideh, Mehdi Jabbari Solanki, Sarika Khushalani

Index Begriffe: Electrical Engineering and Systems Science - Systems and Control, Computer Science - Artificial Intelligence, Computer Science - Machine Learning, text

URL: http://arxiv.org/abs/2406.02927

Photonic analog-to-digital converter powered by a generalized and robust convolutional recurrent autoencoder.

Autoren: Zou X Xu S Deng A et al.

Quelle: Optics express [Opt Express] 2020 Dec 21; Vol. 28 (26), pp. 39618-39628.

Publikationsart: Journal Article

Info zur Zeitschrift: Publisher: Optica Publishing Group Country of Publication: United States NLM ID: 101137103 Publication Model: Print Cited Medium: Internet ISSN: 1094-4087 (Electronic) Linking ISSN: 10944087 NLM ISO Abbreviation: Opt Express Subsets: PubMed not MEDLINE; MEDLINE