Výsledky vyhledávání - sparse convolutional autoencoder (((sace OR sage) OR space))~

A novel multichannel sparse convolutional autoencoder for electrocardiogram signal compression.

Autoři: Bekiryazıcı T Damkacı M Aydemir G a další

Zdroj: Journal of electrocardiology [J Electrocardiol] 2025 Nov-Dec; Vol. 93, pp. 154125. Date of Electronic Publication: 2025 Oct 10.

Způsob vydávání: Journal Article

Informace o časopise: Publisher: Churchill Livingstone Country of Publication: United States NLM ID: 0153605 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1532-8430 (Electronic) Linking ISSN: 00220736 NLM ISO Abbreviation: J Electrocardiol Subsets: MEDLINE

Výrazy ze slovníku MeSH: Electrocardiography*/methods , Data Compression*/methods , Signal Processing, Computer-Assisted* , Neural Networks, Computer*, Humans ; Algorithms ; Autoencoder

Leveraging variant of CAE with sparse convolutional embedding and two-stage application-driven data augmentation for image clustering.

Autoři: Liu, Yanming Liu, Jinglei

Zdroj: Soft Computing - A Fusion of Foundations, Methodologies & Applications. Feb2025, Vol. 29 Issue 3, p1419-1435. 17p.

Témata: *DATA augmentation, *AUTOENCODERS

Reconstructing flow field from sparse sensor data: A deep learning framework combining autoencoder and cross-attention mechanism.

Autoři: Kong, Xuan Fan, Qipei Li, Jinzhao a další

Zdroj: Physics of Fluids. Sep2025, Vol. 37 Issue 9, p1-12. 12p.

Témata: *AUTOENCODERS, *MACHINE learning, *AERODYNAMIC measurements, *ATMOSPHERIC models, *DETECTORS

Deep-Learning-Based Dictionary Construction for MIMO Radar Detection in Complex Scenes

Autoři: Hongyan Wang He Zhou Qinghua Guo a další

Zdroj: IEEE Internet of Things Journal. 11:12419-12434

Témata: nonlinear correction, Multiple-input multiple-output (MIMO) radar, transceiving space-time resource allocation, sparse representation, complex-valued convolutional autoencoder

DLSIA: Deep Learning for Scientific Image Analysis

Autoři: Roberts, Eric J Chavez, Tanny Hexemer, Alexander a další

Zdroj: Journal of Applied Crystallography. 57(2)

Témata: 3402 Inorganic Chemistry (for-2020), 34 Chemical Sciences (for-2020), 3406 Physical Chemistry (for-2020), 51 Physical Sciences (for-2020), 5104 Condensed Matter Physics (for-2020), Bioengineering (rcdc), Biomedical Imaging (rcdc), Machine Learning and Artificial Intelligence (rcdc), Networking and Information Technology R&D (NITRD) (rcdc), deep learning, convolutional neural networks, X-ray scattering, tomography, data compression, X-ray scattering, convolutional neural networks, data compression, deep learning, tomography, 01 Mathematical Sciences (for), 02 Physical Sciences (for), 09 Engineering (for), Inorganic & Nuclear Chemistry (science-metrix), 3402 Inorganic chemistry (for-2020), 3406 Physical chemistry (for-2020), 5104 Condensed matter physics (for-2020)

Popis souboru: application/pdf

Přístupová URL adresa: https://escholarship.org/uc/item/966220w4
https://escholarship.org/content/qt966220w4/qt966220w4.pdf

Application of Artificial Intelligence Technologies as an Intervention for Promoting Healthy Eating and Nutrition in Older Adults: A Systematic Literature Review.

Autoři: Kalu, Kingsley Ataguba, Grace Onifade, Oyepeju a další

Zdroj: Nutrients. Oct2025, Vol. 17 Issue 20, p3223. 33p.

A novel intelligent model for high-precision reconstruction of dam-break free surface profiles from sparse monitoring data.

Autoři: Deng, Yangyu Liu, Yakun Zhang, Di a další

Zdroj: Physics of Fluids. Feb2025, Vol. 37 Issue 2, p1-28. 28p.

Témata: *PROPER orthogonal decomposition, *WATER levels, *AUTOENCODERS, *FREE surfaces, *FLOOD control

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

Autoři: Guo, Shuhan Zhang, Qin Fu, Xiaolong a další

Zdroj: Digital Signal Processing. Jan2026:Part D, Vol. 168, pN.PAG-N.PAG. 1p.

Témata: *DIRECTION of arrival estimation, *CONVOLUTIONAL neural networks, *SPARSE matrices, *MULTIPLE Signal Classification, *FEATURE extraction, *COVARIANCE matrices, *ESTIMATION theory

Real-time forecasting of chaotic dynamics from sparse data and autoencoders

Autoři: Özalp, Elise Nóvoa, Andrea Magri, Luca

Témata: 37N10, 65P20, Chaotic Dynamics, FOS: Physical sciences, Chaotic Dynamics (nlin.CD)

Přístupová URL adresa: http://arxiv.org/abs/2508.08729

3D Segmentation of Perivascular Spaces on T1-Weighted 3 Tesla MR Images With a Convolutional Autoencoder and a U-Shaped Neural Network

Autoři: Philippe Boutinaud Ami Tsuchida Alexandre Laurent a další

Zdroj: Frontiers in Neuroinformatics, Vol 15 (2021)

Témata: perivascular space, deep learning, U-net, MRI, brain cohort, segmentation, Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571

Popis souboru: electronic resource

Relation: https://www.frontiersin.org/articles/10.3389/fninf.2021.641600/full; https://doaj.org/toc/1662-5196

Přístupová URL adresa: https://doaj.org/article/ed3360c8420941b78108600cebb4efc3

Temperature scaling unmixing framework based on convolutional autoencoder

Autoři: Jin Xu Mingming Xu Shanwei Liu a další

Zdroj: International Journal of Applied Earth Observations and Geoinformation, Vol 129, Iss , Pp 103864- (2024)

Témata: Hyperspectral unmixing, Convolutional autoencoder, Sparsity constraint, Temperature scaling, Equal-frequency binning, Physical geography, GB3-5030, Environmental sciences, GE1-350

Popis souboru: electronic resource

Relation: http://www.sciencedirect.com/science/article/pii/S1569843224002188; https://doaj.org/toc/1569-8432

Přístupová URL adresa: https://doaj.org/article/aa7533b7fbf447e1a8b51942e4c8c5f4

Automated Video-EEG Analysis in Epilepsy Studies: A Narrative Review of Advances and Challenges.

Autoři: Zuev VA Salmagambetova EG Djakov SN a další

Zdroj: Journal of medical systems [J Med Syst] 2025 Oct 20; Vol. 49 (1), pp. 142. Date of Electronic Publication: 2025 Oct 20.

Způsob vydávání: Journal Article; Review

Informace o časopise: Publisher: Kluwer Academic/Plenum Publishers Country of Publication: United States NLM ID: 7806056 Publication Model: Electronic Cited Medium: Internet ISSN: 1573-689X (Electronic) Linking ISSN: 01485598 NLM ISO Abbreviation: J Med Syst Subsets: MEDLINE

Výrazy ze slovníku MeSH: Electroencephalography*/methods , Epilepsy*/diagnosis , Epilepsy*/physiopathology , Video Recording*/methods, Humans ; Machine Learning

Application of a Convolutional Autoencoder to Half Space Radar Hrrp Recognition

Autoři: Yong-Jun Xie Shi-Hao Yu

Zdroj: 2018 International Conference on Wavelet Analysis and Pattern Recognition (ICWAPR). :48-53

Témata: 2. Zero hunger, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology, 3. Good health

Přístupová URL adresa: https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8521306
https://ieeexplore.ieee.org/document/8521306/

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

Autoři: Kherad, M. Moayyedi, M. K. Fotouhi-Ghazvini, F. a další

Zdroj: Sensors. 25(16)

Témata: 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

Popis souboru: print

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

3D segmentation of perivascular spaces on T1-weighted 3 Tesla MR images with a convolutional autoencoder and a U-shaped neural network

Autoři: Boutinaud, P. Tsuchida, A. Laurent, A. a další

Zdroj: Frontiers in Neuroinformatics

Popis souboru: application/pdf

Přístupová URL adresa: http://hdl.handle.net/21.11116/0000-000B-12F0-1
http://hdl.handle.net/21.11116/0000-000B-12EE-5

Autoencoders for Semi-Supervised Water Level Modeling in Sewer Pipes with Sparse Labeled Data

Autoři: Rius, Ferran Plana Philipsen, Mark P. Tur, Josep Maria Mirats a další

Zdroj: Rius, F P, Philipsen, M P, Tur, J M M, Moeslund, T B, Bahón, C A & Casas, M 2022, 'Autoencoders for Semi-Supervised Water Level Modeling in Sewer Pipes with Sparse Labeled Data', Water (Switzerland), vol. 14, no. 3, 333. https://doi.org/10.3390/w14030333

Témata: Autoencoders and latent space, Data distribution, Self-supervised, Semi-supervised, Sparse data, Supervised, Water

Popis souboru: application/pdf

Relation: info:eu-repo/semantics/altIdentifier/pissn/2073-4441

Dostupnost: https://vbn.aau.dk/da/publications/65dbf42a-774e-45d2-906a-47e7bd52a17d
https://doi.org/10.3390/w14030333
https://vbn.aau.dk/ws/files/482740247/water_14_00333.pdf
https://www.scopus.com/pages/publications/85123710424

Sparse Representations for Object- and Ego-Motion Estimations in Dynamic Scenes

Autoři: Hirak J. Kashyap Charless C. Fowlkes Jeffrey L. Krichmar

Zdroj: IEEE Transactions on Neural Networks and Learning Systems, vol 32, iss 6

Témata: FOS: Computer and information sciences, Artificial intelligence, Computer Science - Machine Learning, Computer Vision and Pattern Recognition (cs.CV), cs.LG, Computer Science - Computer Vision and Pattern Recognition, ego motion, 02 engineering and technology, Computer Vision and Multimedia Computation, Optical imaging, Machine Learning (cs.LG), Information and Computing Sciences, 0202 electrical engineering, electronic engineering, information engineering, Training, Artificial Intelligence & Image Processing, object motion, sparse representation, cs.CV, overcomplete basis, Cameras, 16. Peace & justice, Dynamics, Convolutional autoencoder, Motion segmentation, Estimation, Adaptive optics

Popis souboru: application/pdf

Přístupová URL adresa: https://escholarship.org/content/qt7p53p8zv/qt7p53p8zv.pdf?t=qgb7mw
https://pubmed.ncbi.nlm.nih.gov/32687472
http://arxiv.org/abs/1903.03731
https://europepmc.org/article/MED/32687472
https://arxiv.org/pdf/1903.03731.pdf
https://arxiv.org/abs/1903.03731
https://par.nsf.gov/biblio/10191836-sparse-representations-object-ego-motion-estimations-dynamic-scenes
https://pubmed.ncbi.nlm.nih.gov/32687472/
https://ui.adsabs.harvard.edu/abs/2019arXiv190303731K/abstract
https://escholarship.org/uc/item/7p53p8zv

3D segmentation of perivascular spaces on T1-weighted 3 Tesla MR images with a convolutional autoencoder and a U-shaped neural network

Autoři: Philippe Boutinaud Ami Tsuchida Alexandre Laurent a další

Zdroj: Front Neuroinform
Frontiers in Neuroinformatics, Vol 15 (2021)

Témata: 03 medical and health sciences, 0302 clinical medicine, segmentation, deep learning, Neurosciences. Biological psychiatry. Neuropsychiatry, perivascular space, U-net, brain cohort, MRI, RC321-571, Neuroscience

Přístupová URL adresa: https://oskar-bordeaux.fr/bitstream/20.500.12278/110227/1/BPH_FN_2021_Boutinaud.pdf
https://www.frontiersin.org/articles/10.3389/fninf.2021.641600/pdf
https://pubmed.ncbi.nlm.nih.gov/34262443
https://doaj.org/article/ed3360c8420941b78108600cebb4efc3
https://biorxiv.org/content/10.1101/2020.11.25.397364v1.full.pdf
https://www.biorxiv.org/content/10.1101/2020.11.25.397364v1

Enhanced heart sound anomaly detection via WCOS: a semi-supervised framework integrating wavelet, autoencoder and SVM.

Autoři: Zeng, Peipei Kang, Shuimiao Fan, Fan a další

Zdroj: Frontiers in Neuroinformatics; 2025, p1-15, 15p

Témata: ANOMALY detection (Computer security), HEART murmurs, SUPPORT vector machines, CONGENITAL heart disease, AUTOENCODERS

Unsupervised learning with sparse space-and-time autoencoders

Autoři: Graham, Benjamin

Témata: Computer Science - Computer Vision and Pattern Recognition, Computer Science - Artificial Intelligence, text

URL: http://arxiv.org/abs/1811.10355