Search Results - "Convolutional autoencoders"

AI-Driven Anomaly Detection in Oscilloscope Images for Post-Silicon Validation

Authors: Akash, Kowshic A. Wulf, Tobias Valentin, Torsten et al.

Source: 2025 38th International Conference on VLSI Design and 2024 23rd International Conference on Embedded Systems (VLSID). :290-295

Subject Terms: Convolutional Autoencoders, Computer Science, Information and General Works::004: Computer Sciences, Artificial Intelligence, MLE@TUHH, Post-Silicon Validation, Anomaly Detection, Technology::621: Applied Physics::621.3: Electrical Engineering, Electronic Engineering

Optimal Transport–Inspired Deep Learning Framework for Slow-Decaying Kolmogorov \({n}\)-Width Problems: Exploiting Sinkhorn Loss and Wasserstein Kernel: Optimal transport-inspired deep learning framework for slow-decaying Kolmogorov \(n\)-width problems: exploiting Sinkhorn loss and Wasserstein kernel

Authors: Khamlich, Moaad Pichi, Federico Rozza, Gianluigi

Source: SIAM Journal on Scientific Computing. 47:C235-C264

Subject Terms: FOS: Computer and information sciences, Computer Science - Machine Learning, Optimal transportation, kernel proper orthogonal decomposition, parameterized PDEs, Computational learning theory, deep learning, Sinkhorn loss, Numerical Analysis (math.NA), Wasserstein distance, convolutional autoencoders, Machine Learning (cs.LG), PDEs on manifolds, FOS: Mathematics, 68T05, 65D99, 41A05, 65N30, 41A46, 90C25, Mathematics - Numerical Analysis, Numerical solution of discretized equations for initial value and initial-boundary value problems involving PDEs, Numerical methods for partial differential equations, initial value and time-dependent initial-boundary value problems, Spectral, collocation and related methods for initial value and initial-boundary value problems involving PDEs, Artificial neural networks and deep learning

File Description: application/xml; application/pdf

Access URL: http://arxiv.org/abs/2308.13840
https://zbmath.org/8005982
https://doi.org/10.1137/23m1604680

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

Authors: G Antoni Gracy Sheena Christabel Pravin

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

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

Access URL: https://doaj.org/article/673f3d321fcf4c7db059c82fb5f3960a

A practical existence theorem for reduced order models based on convolutional autoencoders

Authors: Franco, Nicola Rares Brugiapaglia, Simone

Source: Foundations of Data Science. 7:72-98

Subject Terms: FOS: Computer and information sciences, Computer Science - Machine Learning, Computer Science - Artificial Intelligence, Numerical approximation of high-dimensional functions, sparse grids, Numerical Analysis (math.NA), Theoretical approximation in context of PDEs, 01 natural sciences, parametrized PDEs, Machine Learning (cs.LG), convolutional autoencoders, Artificial Intelligence (cs.AI), FOS: Mathematics, Mathematics - Numerical Analysis, 0101 mathematics, approximation theory, reduced order modeling, Artificial neural networks and deep learning, neural network training

File Description: application/xml

Access URL: http://arxiv.org/abs/2402.00435

Enhancing multi-step-ahead prediction of wave propagation with the CAE-LSTM model: a novel deep learning-based approach to flood dynamics

Authors: Zheng Han Guanping Long Changli Li et al.

Source: Geomatics, Natural Hazards & Risk, Vol 16, Iss 1 (2025)

Subject Terms: Wave propagation, flood dynamics, deep learning, convolutional autoencoders, long short-term memory, Environmental technology. Sanitary engineering, TD1-1066, Environmental sciences, GE1-350, Risk in industry. Risk management, HD61

File Description: electronic resource

Relation: https://doaj.org/toc/1947-5705; https://doaj.org/toc/1947-5713

Access URL: https://doaj.org/article/3e10f6e71d724d5a922f6d9c77ca1330

A deep learning framework for predicting and optimizing flow fields in reactive flows

Authors: Mohsen Gharib Farideh Hoseinian Maleki Philip Rößger et al.

Source: Chemical Engineering Journal Advances, Vol 25, Iss , Pp 100966- (2026)

Subject Terms: Chemical reactors, CFD, Convolutional autoencoders, Neural networks, Multilayer perceptron, Chemical engineering, TP155-156

File Description: electronic resource

Relation: http://www.sciencedirect.com/science/article/pii/S2666821125002601; https://doaj.org/toc/2666-8211

Access URL: https://doaj.org/article/b56db887849c4612a65c36d82a62dbca

Efficient Coupling of Urban Wind Fields and Drone Flight Dynamics Using Convolutional Autoencoders

Authors: Zack Krawczyk Ryan Paul Kursat Kara

Source: Drones, Vol 9, Iss 11, p 802 (2025)

Subject Terms: urban wind fields, urban boundary layer, convolutional autoencoders, Reduced-Order Modeling (ROM), Non-Intrusive ROM, Large-Eddy Simulation (LES), Motor vehicles. Aeronautics. Astronautics, TL1-4050

File Description: electronic resource

Relation: https://www.mdpi.com/2504-446X/9/11/802; https://doaj.org/toc/2504-446X

Access URL: https://doaj.org/article/1d4b41821c8e43b9bcc79eda0400cdc8

Deep Learning for Reduced Sampling Spatial 3-D REM Reconstruction

Authors: Antoni Ivanov Krasimir Tonchev Vladimir Poulkov et al.

Source: IEEE Open Journal of the Communications Society, Vol 5, Pp 2287-2301 (2024)

Subject Terms: neural network design, Telecommunication, 0202 electrical engineering, electronic engineering, information engineering, deep learning, TK5101-6720, 02 engineering and technology, radio environment maps, U-Net, Transportation and communications, reduced sampling, Convolutional autoencoders, HE1-9990

Access URL: https://doaj.org/article/93ee6549a8fd4983ab8422d59448111f

Deep learning-based generation of 4D reference lung volumes for personalized respiratory function assessment

Authors: Vaurs, Damien Maître, Xavier Rodriguez, Dima et al.

Contributors: Vaurs, Damien Maître, Xavier Rodriguez, Dima et al.

Source: EMBC 2025 - IEEE International Conference on Engineering in Medicine and Biology Society ; https://hal.science/hal-05302619 ; EMBC 2025 - IEEE International Conference on Engineering in Medicine and Biology Society, Jul 2025, Copenhague, Denmark ; https://embc.embs.org/2025/

Subject Terms: 3D Spirometry, lung MRI, motion prediction, convolutional autoencoders, recurrent neural networks, Artificial intelligence, [SDV]Life Sciences [q-bio], [INFO]Computer Science [cs], [SPI]Engineering Sciences [physics]

Subject Geographic: Copenhague, Denmark

Relation: info:eu-repo/grantAgreement//101099934/EU/Low and very-low-field 3D magnetic resonance spirometry for advanced regional exploration of respiratory diseases/V-LF-Spiro3D

Availability: https://hal.science/hal-05302619
https://hal.science/hal-05302619v1/document
https://hal.science/hal-05302619v1/file/embc_2025.pdf

Aplicação de métodos de aprendizagem de máquina profunda para redução de ruído em sinais de fala

Authors: Paiva, José Luís Meias Coutinho de Rodrigues, Pedro Miguel de Luís Bispo, Bruno Catarino et al.

Contributors: Paiva, José Luís Meias Coutinho de Rodrigues, Pedro Miguel de Luís Bispo, Bruno Catarino et al.

Source: urn:tid:203904052

Subject Terms: IA, Eco, Reverbação, Ruído, PESQ, Autoencoders convolucionais, AI, Echo, Reverberation, Noise, Convolutional autoencoders

File Description: application/pdf

Availability: http://hdl.handle.net/10400.14/52856

Class-stratified demographics for the autism dataset across sensitive attributes.

Authors: Bin Li Xiaoqian Jiang Kai Zhang et al.

Subject Terms: Biochemistry, Genetics, Biotechnology, Science Policy, Biological Sciences not elsewhere classified, Mathematical Sciences not elsewhere classified, Chemical Sciences not elsewhere classified, Information Systems not elsewhere classified, trained convolutional autoencoders, negative gradients back, multiple sensitive features, extract deep representations, current approaches struggle, clinical decisions ), alzheimer &# 8217, mitigate multiple biases, mdann approach leads, enhance prediction accuracy, equitable disease prediction, prediction outcome, ensure equitable, disease prediction, better accuracy, enhance fairness, utilize pre, unfair treatment, reliable outcomes, provide reliable, minority groups, medical predictions

Availability: https://doi.org/10.1371/journal.pdig.0000830.s002
https://figshare.com/articles/journal_contribution/Class-stratified_demographics_for_the_autism_dataset_across_sensitive_attributes_/29200623

Efficient Compression of Red Blood Cell Image Dataset Using Joint Deep Learning-Based Pattern Classification and Data Compression

Authors: Zerin Nusrat Md Firoz Mahmud W. David Pan

Source: Electronics ; Volume 14 ; Issue 8 ; Pages: 1556

Subject Terms: lossy compression, deep learning, stacked autoencoders, vision transformers, image classification, convolutional autoencoders, Malaria

File Description: application/pdf

Relation: Computer Science & Engineering; https://dx.doi.org/10.3390/electronics14081556

Availability: https://doi.org/10.3390/electronics14081556

Defect Detection for Enhanced Traceability in Naval Construction

Authors: Paula Arcano-Bea Manuel Rubiños Agustín García-Fischer et al.

Source: Sensors ; Volume 25 ; Issue 4 ; Pages: 1077

Subject Terms: convolutional autoencoders (CAEs), anomaly detection, shipbuilding, quality control, unsupervised learning

File Description: application/pdf

Relation: Fault Diagnosis & Sensors; https://dx.doi.org/10.3390/s25041077

Availability: https://doi.org/10.3390/s25041077

Convolutional Autoencoders, Clustering, and Pod for Low-Dimensional Parametrization of Flow Equations: Convolutional autoencoders, clustering, and POD for low-dimensional parametrization of flow equations

Authors: Heiland, Jan Kim, Yongho

Source: Computers & Mathematics with Applications. 175:49-61

Subject Terms: convolutional autoencoders, linear parameter varying systems, model order reduction, linear parameter varying (LPV) systems, Fluid mechanics, Partial differential equations, clustering

File Description: application/xml

Deep learning of movement behavior profiles and their association with markers of cardiometabolic health

Authors: Vahid Farrahi Paul J Collings Mourad Oussalah

Source: BMC Medical Informatics and Decision Making, Vol 24, Iss 1, Pp 1-16 (2024)

Subject Terms: Convolutional autoencoders, Cardiometabolic health, Clustering, Accelerometry, Wearables, Computer applications to medicine. Medical informatics, R858-859.7

File Description: electronic resource

Relation: https://doaj.org/toc/1472-6947

Access URL: https://doaj.org/article/409caaf3c7794d5fbcae4b34c0a6aad2

On the Dimensionality and Utility of Convolutional Autoencoder’s Latent Space Trained with Topology-Preserving Spectral EEG Head-Maps

Authors: Arjun Vinayak Chikkankod Luca Longo

Source: Machine Learning and Knowledge Extraction, Vol 4, Iss 4, Pp 1042-1064 (2022)
Machine Learning and Knowledge Extraction; Volume 4; Issue 4; Pages: 1042-1064
Articles

Subject Terms: Computer engineering. Computer hardware, automatic feature extraction, Electroencephalography, sliding windowing, 02 engineering and technology, TK7885-7895, convolutional autoencoders, 03 medical and health sciences, 0302 clinical medicine, latent space analysis, dense neural network, electroencephalography, 0202 electrical engineering, electronic engineering, information engineering, Computer Engineering

File Description: application/pdf

Access URL: https://doaj.org/article/07f3eba3256e49f2b22718c444616f19
https://researchprofiles.tudublin.ie/en/publications/543ab974-21e5-4738-bf5a-d0209e3c5312
https://doi.org/10.3390/make4040053
https://arrow.tudublin.ie/scschcomart/175

An Application of Deep Learning Technique to Improve Subseasonal to Seasonal Rainfall Forecast over Java Island, Indonesia

Authors: Adyaksa Budi Raharja Akhmad Faqih Amsari Mudzakir Setiawan

Source: Journal of Natural Resources and Environmental Management, Vol 12, Iss 4 (2022)

Subject Terms: Environmental sciences, 13. Climate action, GE1-350, 15. Life on land, bias correction, convolutional autoencoders, rainfall forecasts, sub-seasonal to seasonal, 6. Clean water

Access URL: https://doaj.org/article/3ee2eda13e0f47a194be2438e8a658c5

Convolutional Autoencoders and Clustering for Low-dimensional Parametrization of Incompressible Flows

Authors: Heiland, Jan Kim, Yongho

Source: IFAC-Papers

Subject Terms: convolutional autoencoders, 0209 industrial biotechnology, model reduction, 0202 electrical engineering, electronic engineering, information engineering, incompressible flows, linear parameter-varying systems, 02 engineering and technology, clustering

File Description: application/pdf

Access URL: http://hdl.handle.net/21.11116/0000-000B-9F9A-5
http://hdl.handle.net/21.11116/0000-000B-9FAB-2

Automated SAT Problem Feature Extraction using Convolutional Autoencoders

Authors: Dalla, Marco Visentin, Andrea O'Sullivan, Barry

Source: 2021 IEEE 33rd International Conference on Tools with Artificial Intelligence (ICTAI). :232-239

Subject Terms: CNF encoding, N-P complete problem, SAT problem, Feature extraction, Deep learning, Satisfiability prediction, Autoencoders, Boolean Satisfiability Problem (SAT), Boolean satisfiability, Convolutional autoencoders

File Description: application/pdf

Access URL: http://hdl.handle.net/10468/13554
http://hdl.handle.net/10468/12238

Interpolation of Irregularly Sampled Frequency Response Functions Using Convolutional Neural Networks

Authors: Acerbi M. Malvermi R. Pezzoli M. et al.

Source: ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). :950-954

Subject Terms: Irregular sampling, 0202 electrical engineering, electronic engineering, information engineering, Spatial interpolation, 02 engineering and technology, Frequency response function, Convolutional autoencoders

Access URL: https://dblp.uni-trier.de/db/conf/icassp/icassp2021.html#AcerbiMPASC21
https://ieeexplore.ieee.org/document/9413458/