Suchergebnisse - Reduced Conventional Autoencoder

Robustness evaluation of large-scale machine learning-based reduced order models for reproducing flow fields.

Autoren: Higashida, Aito Ando, Kazuto Rüttgers, Mario et al.

Quelle: Future Generation Computer Systems. Oct2024, Vol. 159, p243-254. 12p.

Schlagwörter: *ARTIFICIAL neural networks, REDUCED-order models, PROPER orthogonal decomposition, SQUARE waves, NONLINEAR equations, MACHINE performance, MULTIPLE access protocols (Computer network protocols)

Autoencoder-Based DIFAR Sonobuoy Signal Transmission and Reception Method Incorporating Residual Vector Quantization and Compensation Module: Validation Through Air Channel Modeling.

Autoren: Park, Yeonjin Hong, Jungpyo

Quelle: Applied Sciences (2076-3417); Jan2025, Vol. 15 Issue 1, p92, 21p

Schlagwörter: VECTOR quantization, SIGNAL reconstruction, AUTOENCODERS, SIGNALS & signaling

A Scalable Hybrid Autoencoder–Extreme Learning Machine Framework for Adaptive Intrusion Detection in High-Dimensional Networks.

Autoren: Kumar, Anubhav Radhakrishnan, Rajamani Sumithra, Mani et al.

Quelle: Future Internet. May2025, Vol. 17 Issue 5, p221. 18p.

Schlagwörter: *Machine learning, Extreme learning machines, Autoencoder, Blended learning, Infrastructure (Economics)

Combining variational autoencoders with generative adversarial networks to adaptively adjust the electromagnetic compatibility of biomechanical data analysis platforms.

Autoren: Sun, Hongyan Zhu, Mingxiang Wang, Xingbo

Quelle: Molecular & Cellular Biomechanics; 2025, Vol. 22 Issue 5, p1-17, 17p

Schlagwörter: ELECTROMAGNETIC compatibility, GENERATIVE adversarial networks, PROBABILISTIC generative models, DATA augmentation, BIOMECHANICS, WEARABLE technology, ELECTROMAGNETIC interference

Sensor-Driven Surrogate Modeling and Control of Nonlinear Dynamical Systems Using FAE-CAE-LSTM and Deep Reinforcement Learning

Autoren: Kherad, M. Moayyedi, M. K. Fotouhi-Ghazvini, F. et al.

Quelle: Sensors. 25(16)

Schlagwörter: Autoencoders, Control Of Dynamical Systems, Cyber-physical Systems, Deep Reinforcement Learning, Long Short-term Memory, Sensor-driven Modeling, Circular Cylinders, Computer Control Systems, Convolution, Dynamical Systems, Dynamics, Embedded Systems, Flow Control, Fuel Additives, Nonlinear Dynamical Systems, Real Time Control, Robust Control, Auto Encoders, Control Of Dynamical System, Cybe-physical Systems, High-dimensional, Higher-dimensional, Reinforcement Learning Agent, Reinforcement Learnings, Short Term Memory

Dateibeschreibung: print

Zugangs-URL: https://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-73172
https://doi.org/10.3390/s25165149

Comparing Functional and Effective Connectivity Features in Diagnosis of Autism Spectrum Disorder Using Stacked Autoencoder by Resting-State fMRI Data.

Autoren: Navaei, Pegah Khadem, Ali Zaferani, Effat Jalaeian

Quelle: Frontiers in Biomedical Technologies; Autumn2025, Vol. 12 Issue 4, p830-843, 14p

Schlagwörter: AUTISM spectrum disorders, FUNCTIONAL connectivity, AUTOENCODERS, ARTIFICIAL neural networks, FUNCTIONAL magnetic resonance imaging, GRANGER causality test

Feature Extraction With Stacked Autoencoders for EEG Channel Reduction in Emotion Recognition.

Autoren: Vafaei, Elnaz Rahatabad, Fereidoun Nowshiravan Setarehdan, Seyed Kamaledin et al.

Quelle: Basic & Clinical Neuroscience; May/Jun2024, Vol. 15 Issue 3, p393-402, 10p

Schlagwörter: EMOTION recognition, SUPPORT vector machines, DEEP learning, FEATURE extraction, ELECTROENCEPHALOGRAPHY

AE-BoNet: A Deep Learning Method for Pediatric Bone Age Estimation using an Unsupervised Pre-Trained Model.

Autoren: Sirati-Amsheh, Mojtaba Shabaninia, Elham Chaparian, Ali

Quelle: Journal of Biomedical Physics & Engineering; Jun2025, Vol. 15 Issue 3, p271-280, 10p

Schlagwörter: CONVOLUTIONAL neural networks, DEEP learning, AUTOENCODERS, X-ray imaging, BONE measurement

Detecting network intrusions in cyber-physical systems using deep autoencoder-based dimensionality reduction approach and deep neural networks.

Autoren: Ibor, A. E. Egete, D. O. Otiko, A. O. et al.

Quelle: Journal of Nigerian Society of Physical Sciences; Aug2025, Vol. 7 Issue 3, p1-15, 15p

Schlagwörter: ARTIFICIAL neural networks, FEEDFORWARD neural networks, AUTOENCODERS, CYBER physical systems, COMPUTER network traffic, DEEP learning

Graph-Variational Convolutional Autoencoder-Based Fault Detection and Diagnosis for Photovoltaic Arrays.

Autoren: Arifeen, Murshedul Petrovski, Andrei Hasan, Md Junayed et al.

Quelle: Machines; Dec2024, Vol. 12 Issue 12, p894, 15p

Schlagwörter: SOLAR cells, RENEWABLE energy sources, PHOTOVOLTAIC power systems, SOLAR energy, AUTOENCODERS

Model‐Reduced Adjoint‐Based Inversion Using Deep‐Learning: Example of Geological Carbon Sequestration Modeling.

Autoren: Xiao, Cong Zhang, Shicheng Ma, Xinfang et al.

Quelle: Water Resources Research; Jan2022, Vol. 58 Issue 1, p1-27, 27p

Schlagwörter: GEOLOGICAL carbon sequestration, MULTIPHASE flow, FINITE difference method, REDUCED-order models, GEOLOGICAL modeling, DEEP learning, MAGNITUDE (Mathematics), WORKFLOW

Autoencoder-based confidence score for item preknowledge detection.

Autoren: Pan, Yiqin

Quelle: Behaviormetrika; Jul2025, Vol. 52 Issue 2, p317-342, 26p

Schlagwörter: AUTOENCODERS, DEEP learning, PRIOR learning, SIMULATION methods & models, DETECTION algorithms, SIGNAL detection, TEST design

Deep Learning-Based Risk Assessment and Prediction of Cardiac Outcomes Using Single-Lead 24-Hour Holter-ECG in Patients with Heart Failure or Myocardial Infarction.

Autoren: Kim, Ju Youn Kim, Kyung Geun Joo, Sunghoon et al.

Quelle: Journal of Clinical Medicine; Oct2025, Vol. 14 Issue 20, p7209, 13p

Schlagwörter: DEEP learning, HEART failure, NONINVASIVE diagnostic tests, RISK assessment, AMBULATORY electrocardiography, MAJOR adverse cardiovascular events, MYOCARDIAL infarction

Prediction of Recurrence using a Stacked Denoising Autoencoder and Multifaceted Feature Analysis of Pretreatment MRI in Patients with Nasopharyngeal Carcinoma.

Autoren: Liu Y Wang X Li J et al.

Quelle: Current radiopharmaceuticals [Curr Radiopharm] 2025; Vol. 18 (3), pp. 224-243.

Publikationsart: Journal Article

Info zur Zeitschrift: Publisher: Bentham Science Publishers Country of Publication: United Arab Emirates NLM ID: 101468718 Publication Model: Print Cited Medium: Internet ISSN: 1874-4729 (Electronic) Linking ISSN: 18744710 NLM ISO Abbreviation: Curr Radiopharm Subsets: MEDLINE

MeSH-Schlagworte: Nasopharyngeal Carcinoma*/diagnostic imaging , Nasopharyngeal Carcinoma*/radiotherapy , Nasopharyngeal Carcinoma*/pathology , Magnetic Resonance Imaging*/methods , Neoplasm Recurrence, Local*/diagnostic imaging , Nasopharyngeal Neoplasms*/diagnostic imaging , Nasopharyngeal Neoplasms*/radiotherapy , Nasopharyngeal Neoplasms*/pathology, Humans ; Female ; Male ; Middle Aged ; Adult ; Retrospective Studies ; Radiotherapy, Intensity-Modulated ; Aged ; Deep Learning ; Autoencoder

Optimizing dotted Arabic expiration date recognition with ARABEX: a convolutional autoencoder with bidirectional LSTM and CRNN approach.

Autoren: Zaki, Hozaifa Soliman, Ghada

Quelle: International Journal on Document Analysis & Recognition; Dec2025, Vol. 28 Issue 4, p555-572, 18p

Intelligent Differentiation Framework for Lewy Body Dementia and Alzheimer's Disease Using Adaptive Multi-Cascaded ResNet–Autoencoder–LSTM Network.

Autoren: Sravani, K. RaviSankar, V.

Quelle: International Journal of Image & Graphics; Nov2025, Vol. 25 Issue 6, p1-30, 31p

Hierarchical Deep Learning for Abnormality Classification in Mouse Skeleton Using Multiview X-Ray Images: Convolutional Autoencoders Versus ConvNeXt.

Autoren: Jawaid, Muhammad M. Bains, Rasneer S. Wells, Sara et al.

Quelle: Journal of Imaging; Oct2025, Vol. 11 Issue 10, p348, 23p

Autoencoder with Constraints for Subsurface Defect Detection in Quadratic Frequency Modulated Thermal Wave Imaging.

Autoren: Bandari, Enosh Oleti, Siva Subrahmanyam Prasanthi, Y. Naga et al.

Quelle: Sensing & Imaging; 8/18/2025, Vol. 26 Issue 1, p1-17, 17p

Multi-scale asynchronous correlation and 2D convolutional autoencoder for adolescent health risk prediction with limited fMRI data.

Autoren: Di Gao Guanghao Yang Jiarun Shen et al.

Quelle: Frontiers in Computational Neuroscience; 2024, p01-12, 12p

Schlagwörter: HEALTH risk assessment, FUNCTIONAL magnetic resonance imaging, VALUE engineering, EXTRACTION techniques, DATA mining

Harnessing Generative Deep Learning for Enhanced Ensemble Data Assimilation.

Autoren: Foroumandi, Ehsan Moradkhani, Hamid

Quelle: Water Resources Research; Jul2025, Vol. 61 Issue 7, p1-25, 25p

Schlagwörter: DATA assimilation, HYDROLOGIC models, GENERATIVE artificial intelligence, AUTOENCODERS