Suchergebnisse - Autoencoder neural network

Fine-Tuned Autoencoder Neural Network for Anomaly Detection in Accounting Transactions

Autoren: null Nur Alamsyah Hani Fitria Rahmani Wala Erpurini et al.

Quelle: Paradigma - Jurnal Komputer dan Informatika. 27:65-73

Anomaly Detection for HVAC System Maintenance Using Autoencoder Neural Network

Autoren: D. Borić T. Hadjina L. Luttenberger Marić

Quelle: 2024 47th MIPRO ICT and Electronics Convention (MIPRO). :1855-1858

Schlagwörter: autoencoder neural network, HVAC, anomaly detection, maintenance

Zugangs-URL: https://ieeexplore.ieee.org/document/10569903/
https://doi.org/10.1109/mipro60963.2024.10569903

Anomaly Detection in Containerized Systems Based on System Call Histograms and Autoencoder Neural Network

Autoren: Igor Kotenko Maxim Melnik

Quelle: 2025 IEEE 26th International Conference of Young Professionals in Electron Devices and Materials (EDM). :1510-1514

VLSI Architecture Design for Compact Shortcut Denoising Autoencoder Neural Network of ECG Signal

Autoren: Shin-Chi Lai Szu-Ting Wang S. M. Salahuddin Morsalin et al.

Quelle: IEEE Transactions on Circuits and Systems I: Regular Papers. 72:1621-1633

Integrative Analysis of Heterogeneous Cancer Data Using Autoencoder Neural Networks

Autoren: null Mia Md Tofayel Gonee Manik

Quelle: Journal of Information Systems Engineering and Management. 10:548-554

'Optimizing sEMG Gesture Recognition with Stacked Autoencoder Neural Network for Bionic Hand'

Autoren: Mr. Amol Pandurang Yadav Dr. Sandip.R. Patil

Quelle: MethodsX, Vol 14, Iss , Pp 103207- (2025)

Schlagwörter: Stacked autoencoder neural network (SAE), Science

Dateibeschreibung: electronic resource

Relation: http://www.sciencedirect.com/science/article/pii/S221501612500055X; https://doaj.org/toc/2215-0161

Zugangs-URL: https://doaj.org/article/1aa5844d9d61416192f0e3ae736c041f

Hybrid Method of Non-invasive Intracranial Pressure Measurement Using Autoencoder Neural Network Algorithm

Autoren: M. Bohdanowicz D. Cardim B. Schmidt et al.

Quelle: Acta Physica Polonica A. 146:349-354

Traffic Image Analysis Based on Stacked Denoising Autoencoder Neural Network

Autoren: Daehyon Kim

Quelle: Journal of Innovation Information Technology and Application, Vol 5, Iss 2, Pp 183-192 (2023)

Schlagwörter: autoencoding, deep belief network, neural network, Electronic computers. Computer science, 0502 economics and business, 05 social sciences, stacked denoising, 0202 electrical engineering, electronic engineering, information engineering, Information technology, QA75.5-76.95, 02 engineering and technology, T58.5-58.64, backpropagation

Zugangs-URL: https://doaj.org/article/fabc870fc1524bf4a89ecb4aaed0ca7a

Segmentation of MR images for brain tumor detection using autoencoder neural network

Autoren: Farnaz Hoseini Shohreh Shamlou Milad Ahmadi-Gharehtoragh

Quelle: Discover Artificial Intelligence, Vol 4, Iss 1, Pp 1-20 (2024)

Schlagwörter: Autoencoder neural network, MR images, Segmentation, MRI, Brain tumor detection, Autoencoder, Computational linguistics. Natural language processing, P98-98.5, Electronic computers. Computer science, QA75.5-76.95

Dateibeschreibung: electronic resource

Relation: https://doaj.org/toc/2731-0809

Zugangs-URL: https://doaj.org/article/e34b7cf1b51e4f0e9b29bd610cc26b96

Generation of Orthogonal THz Pulses for Wireless Communications Based on Diffractive Autoencoder Neural Networks

Autoren: Xin Wang Xudong Wang

Quelle: IEEE Transactions on Machine Learning in Communications and Networking, Vol 3, Pp 1210-1226 (2025)

Schlagwörter: Terahertz (THz) communications, pulse generator, diffractive surface, neural network, Electronic computers. Computer science, QA75.5-76.95, Telecommunication, TK5101-6720

Dateibeschreibung: electronic resource

Relation: https://ieeexplore.ieee.org/document/11231335/; https://doaj.org/toc/2831-316X

Zugangs-URL: https://doaj.org/article/18a227131d554dccb78995b1ef956096

Sahand: A Software Fault-Prediction Method Using Autoencoder Neural Network and K-Means Algorithm

Autoren: Bahman Arasteh Sahar Golshan Shiva Shami et al.

Quelle: Journal of Electronic Testing. 40:229-243

Schlagwörter: 0202 electrical engineering, electronic engineering, information engineering, K-Means, Autoencoder, 02 engineering and technology, Software Fault Prediction, Clustering, Accuracy

Zugangs-URL: https://hdl.handle.net/20.500.12713/5581

A One‐Class Autoencoder Neural Network Approach for Rapid Raman‐Based Pharmaceutical Quality Screening.

Autoren: Galeeva, Ekaterina V. Galeev, Roman R. Khokhlov, Alexander l. et al.

Quelle: Journal of Raman Spectroscopy. Oct2025, p1. 10p. 8 Illustrations.

Schlagwörter: *RAMAN spectroscopy, *AUTOENCODERS, *OUTLIER detection, *DATA augmentation, *QUALITY control, *DIMENSIONAL reduction algorithms, *MEDICATION safety, *DRUG development

CFDSAEDDA: A Collaborative Filtering and Deep Sparse Autoencoder Neural Network Method for Inferring Drug-Disease Associations

Autoren: Van Tinh Nguyen Minh Yen Vu Thi Bich Thuy Ngo et al.

Quelle: Lecture Notes in Networks and Systems ISBN: 9783031809422

AUTOENCODER NEURAL NETWORK FOR UNIVARIATE TIME SERIES EMBEDDING

Autoren: Eugene Koshel

Quelle: International scientific and technical conference Information technologies in metallurgy and machine building. :266-269

Thyroid Nodule Diagnosis Using a New Supervised Autoencoder Neural Network with $$\ell _{1,\infty }$$ Projection

Autoren: Grégoire D’Andrea Cyprien Gille Thierry Pourcher et al.

Quelle: Lecture Notes in Computer Science ISBN: 9783031907135

Cascade stacked autoencoder neural network for intrusion detection in CAN-FD vehicular network

Autoren: V. Anjana Devi P.V. Bhaskar Reddy Sreenu Ponnada et al.

Quelle: Knowledge-Based Systems. 329:114301

The dynamics of field soil water retention curves predicted by autoencoder neural network

Autoren: Nedal Aqel Andrea Carminati Peter Lehmann

Schlagwörter: 15. Life on land, 6. Clean water

Prediction of hysteretic matric potential dynamics using artificial intelligence: application of autoencoder neural networks

Autoren: N. Aqel L. Reusser S. Margreth et al.

Quelle: eISSN
Geoscientific Model Development, Vol 17, Pp 6949-6966 (2024)
Geoscientific Model Development, 17 (18)
Geoscientific Model Development

Schlagwörter: 2. Zero hunger, QE1-996.5, Geology, 15. Life on land

Dateibeschreibung: application/pdf; application/application/pdf

Zugangs-URL: https://gmd.copernicus.org/articles/17/6949/2024/
https://egusphere.copernicus.org/preprints/2024/egusphere-2024-407/
https://doaj.org/article/97876182f77c4f338513209b2a4d7def
http://hdl.handle.net/20.500.11850/695388

LSTMED: An uneven dynamic process monitoring method based on LSTM and Autoencoder neural network

Autoren: Wenfeng, Deng Yuxuan, Li Keke, Huang et al.

Quelle: Neural Networks. 158:30-41

Schlagwörter: Spatial Analysis, 0209 industrial biotechnology, Memory, Long-Term, 0202 electrical engineering, electronic engineering, information engineering, Computer Simulation, Neural Networks, Computer, 02 engineering and technology

Zugangs-URL: https://pubmed.ncbi.nlm.nih.gov/36442372

Learning particle dynamics: from diffusion to interactions

Autoren: Fernández Fernández, Gabriel

Weitere Verfasser: University/Department: Universitat Politècnica de Catalunya. Institut de Ciències Fotòniques

Thesis Advisors: Lewenstein, Maciej, Manzo, Carlo

Quelle: TDX (Tesis Doctorals en Xarxa)

Schlagwörter: Unsupervised, Machine Learning, Variational Autoencoder, Feature Learning, Representation Learning, Autoregressive Model, Data Analysis, Knowledge Discovery, Interpretability, Biophysics, Anomalous Diffusion, Single Trajectory Characterization, Time Series, Stochastic Model, Brownian Motion, Fractional Brownian Motion, Scaled Brownian Motion, Confined Brownian Motion, Graph Neural Network, Lennard-Jones, Non-reciprocal Force, Àrees temàtiques de la UPC::Enginyeria de la telecomunicació, Àrees temàtiques de la UPC::Informàtica, 621.3 - Enginyeria elèctrica. Electrotècnia. Telecomunicacions, 004 - Informàtica, 577 - Bioquímica. Biologia molecular. Biofísica

Dateibeschreibung: application/pdf

Zugangs-URL: http://hdl.handle.net/10803/696076
https://dx.doi.org/10.5821/dissertation-2117-448803