Výsledky vyhľadávania - conditioning variational autoencoder(cae)

Self‐supervised representation learning of metro interior noise based on variational autoencoder and deep embedding clustering.

Autori: Wang, Yang Xiao, Hong Zhang, Zhihai a ďalší

Zdroj: Computer-Aided Civil & Infrastructure Engineering; 2/4/2025, Vol. 40 Issue 4, p503-522, 20p

Predmety: TRANSPORTATION noise, SIGNAL denoising, PATTERN perception, FAULT diagnosis, LATENT variables, MACHINE learning, EMPIRICAL research

Adaptive Neural Network System for Detecting Unauthorised Intrusions Based on Real-Time Traffic Analysis.

Autori: Vladov, Serhii Vysotska, Victoria Lytvyn, Vasyl a ďalší

Zdroj: Computation; Sep2025, Vol. 13 Issue 9, p221, 42p

Predmety: INTRUSION detection systems (Computer security), ANOMALY detection (Computer security), KALMAN filtering, LATENT variables, INTERNET security, TRAFFIC monitoring, MACHINE learning, INTELLIGENT networks

Heartbeat detection and personal authentication using a 60 GHz Doppler sensor.

Autori: Asano, Takuma Izumi, Shintaro Kawaguchi, Hiroshi

Zdroj: Frontiers in Digital Health; 2025, p1-12, 12p

Predmety: PATIENT monitoring equipment, BIOLOGICAL models, RESEARCH funding, SOUND spectrography, BIOMETRY, HEART beat, ELECTROCARDIOGRAPHY, SECURITY systems, TECHNOLOGY, PATIENT monitoring, MICROWAVES, WAVE analysis, ALGORITHMS

Human Activity Recognition Using Convolutional Autoencoder and Advanced Preprocessing.

Autori: Zaoui, Chaimae Benabbou, Faouzia Ettaoufik, Abdelaziz a ďalší

Zdroj: International Journal of Online & Biomedical Engineering; 2024, Vol. 20 Issue 4, p144-159, 16p

Convolutional Autoencoder Based Feature Extraction and Clustering for Customer Load Analysis.

Autori: Ryu, Seunghyoung Choi, Hyungeun Lee, Hyoseop a ďalší

Zdroj: IEEE Transactions on Power Systems; Mar2020, Vol. 35 Issue 2, p1048-1060, 13p

Predmety: FEATURE extraction, DEEP learning, ARTIFICIAL neural networks, DATA compression, SMART meters, DATA transmission systems

Variational autoencoders for 3D data processing.

Autori: Molnár, Szilárd Tamás, Levente

Zdroj: Artificial Intelligence Review; Feb2024, Vol. 57 Issue 2, p1-53, 53p

Health Prognostics Classification with Autoencoders for Predictive Maintenance of HVAC Systems.

Autori: Tian, Ruiqi Gomez-Rosero, Santiago Capretz, Miriam A. M.

Zdroj: Energies (19961073); Oct2023, Vol. 16 Issue 20, p7094, 21p

Predmety: AIR filters, HEATING, AIR ducts, HEATING & ventilation industry, ENVIRONMENTAL quality

Enhancing Automotive Paint Curing Process Efficiency: Integration of Computational Fluid Dynamics and Variational Auto-Encoder Techniques.

Autori: Pendar, Mohammad-Reza Cândido, Silvio Páscoa, José Carlos a ďalší

Zdroj: Sustainability (2071-1050); Apr2025, Vol. 17 Issue 7, p3091, 35p

Continual learning approaches for anomaly detection.

Autori: Pezze, Davide Dalle Anello, Eugenia Masiero, Chiara a ďalší

Zdroj: Evolving Systems; Dec2025, Vol. 16 Issue 4, p1-20, 20p

A Review of Human Emotion Synthesis Based on Generative Technology.

Autori: Ma, Fei Xie, Yifan Li, Yukan a ďalší

Zdroj: IEEE Transactions on Affective Computing; Oct-Dec2025, Vol. 16 Issue 4, p2579-2598, 20p

Universal Physiological Representation Learning With Soft-Disentangled Rateless Autoencoders.

Autori: Han, Mo Ozdenizci, Ozan Koike-Akino, Toshiaki a ďalší

Zdroj: IEEE Journal of Biomedical & Health Informatics; Aug2021, Vol. 25 Issue 8, p2928-2937, 10p

Predmety: DEEP learning, PATIENT monitoring, SOCIAL interaction, FEATURE extraction

Time Series Prediction for Cycling Sport Performance Through a Machine Learning Predictor.

Autori: Mohd Nawi, Muhammad Zulazri Hanis Sudin, Sukhairi Ahmad Saad, Fathinul Syahir a ďalší

Zdroj: Pertanika Journal of Science & Technology; Oct2025, Vol. 33 Issue 6, p2685-2722, 38p

Predmety: CYCLING, MACHINE learning, DEEP learning, SPORTS forecasting, SPORTS statistics, ARTIFICIAL intelligence, LONG short-term memory, FORECASTING

A Modular Perspective on the Evolution of Deep Learning: Paradigm Shifts and Contributions to AI.

Autori: Wei, Yicheng Wang, Yifu Watada, Junzo

Zdroj: Applied Sciences (2076-3417); Oct2025, Vol. 15 Issue 19, p10539, 38p

Predmety: DEEP learning, ARTIFICIAL intelligence, OPTIMIZATION algorithms, RESEARCH methodology, SCALABILITY, LANGUAGE models, TECHNOLOGICAL innovations

Machine Learning for Structural Health Monitoring of Aerospace Structures: A Review.

Autori: Scarselli, Gennaro Nicassio, Francesco

Zdroj: Sensors (14248220); Oct2025, Vol. 25 Issue 19, p6136, 46p

Predmety: MACHINE learning, STRUCTURAL health monitoring, FAILURE analysis, DIGITAL twin, DATA acquisition systems, KNOWLEDGE transfer, AIRFRAMES

Autoencoder-based image processing framework for object appearance modifications.

Autori: Ślot, Krzysztof Kapusta, Paweł Kucharski, Jacek

Zdroj: Neural Computing & Applications; Feb2021, Vol. 33 Issue 4, p1079-1090, 12p

Predmety: PRINCIPAL components analysis, IMAGE processing, DATA mining, HUMAN facial recognition software

Multiphase flow applications of nonintrusive reduced-order models with Gaussian process emulation.

Autori: Botsas, Themistoklis Pan, Indranil Mason, Lachlan R. a ďalší

Zdroj: Data-Centric Engineering; 2022, Vol. 3, p1-21, 21p

Predmety: MULTIPHASE flow, SHORT-term memory, GAUSSIAN processes, PIPELINES, METHODOLOGY

A Survey of Traditional and Emerging Deep Learning Techniques for Non-Intrusive Load Monitoring.

Autori: Huzzat, Annysha Khwaja, Ahmed S. Alnoman, Ali A. a ďalší

Zdroj: AI; Sep2025, Vol. 6 Issue 9, p213, 50p

Predmety: DEEP learning, ARTIFICIAL intelligence, SMART meters, ENERGY consumption, GENERATIVE artificial intelligence

Designing metamaterials with programmable nonlinear responses and geometric constraints in graph space.

Autori: Maurizi, Marco Xu, Derek Wang, Yu-Tong a ďalší

Zdroj: Nature Machine Intelligence; Jul2025, Vol. 7 Issue 7, p1023-1036, 14p

Deep learning architectures for data-driven damage detection in nonlinear dynamic systems under random vibrations.

Autori: Joseph, Harrish Quaranta, Giuseppe Carboni, Biagio a ďalší

Zdroj: Nonlinear Dynamics; Dec2024, Vol. 112 Issue 23, p20611-20636, 26p

Deep Learning for Time Series Anomaly Detection: A Survey.

Autori: Zamanzadeh Darban, Zahra Webb, Geoffrey I. Pan, Shirui a ďalší

Zdroj: ACM Computing Surveys; Jan2025, Vol. 57 Issue 1, p1-42, 42p

Predmety: ARTIFICIAL neural networks, ARTIFICIAL intelligence, REINFORCEMENT learning, CONVOLUTIONAL neural networks, GRAPH neural networks, DEEP learning, SUPERVISED learning