Suchergebnisse - multi-scale conventional current variational autoencoder*

Spatial-Frequency-Scale Variational Autoencoder for Enhanced Flow Diagnostics of Schlieren Data.

Autoren: Yang, Ronghua Wu, Hao Yang, Rongfei et al.

Quelle: Sensors (14248220); Oct2025, Vol. 25 Issue 19, p6233, 29p

Schlagwörter: FLUID dynamics, AUTOENCODERS, FLOW visualization, FOURIER transforms, DEEP learning, FEATURE extraction, FORECASTING

Self-Organizing Maps-Assisted Variational Autoencoder for Unsupervised Network Anomaly Detection.

Autoren: Huang, Hailong Yang, Jiahong Zeng, Hang et al.

Quelle: Symmetry (20738994); Apr2025, Vol. 17 Issue 4, p520, 15p

Schlagwörter: DETECTION algorithms, SELF-organizing maps, FEATURE selection, ANOMALY detection (Computer security), AUTOENCODERS

Personalized design aesthetic preference modeling: a variational autoencoder and meta-learning approach for multi-modal feature representation and transfer optimization.

Autoren: Chen, Chengliang Gong, Zhiqun

Quelle: Scientific Reports; 11/24/2025, Vol. 15 Issue 1, p1-19, 19p

Schlagwörter: AESTHETIC judgment, FEATURE extraction, CUSTOM design, KNOWLEDGE transfer, MACHINE learning

Research on Mechanical Fault Diagnosis Method of Isolation Switch Based on Variational Autoencoder.

Autoren: He, Shun Zhou, Fangrong Tan, Xiangyu et al.

Quelle: Processes; Aug2025, Vol. 13 Issue 8, p2388, 17p

Schlagwörter: FAULT diagnosis, OUTLIER detection, REAL-time computing, PROBABILISTIC generative models, HIGH voltages, CONDITION-based maintenance, GALVANIC isolation, MACHINE learning

Multi-Channel Multi-Scale Convolution Attention Variational Autoencoder (MCA-VAE): An Interpretable Anomaly Detection Algorithm Based on Variational Autoencoder.

Autoren: Liu, Jingwen Huang, Yuchen Wu, Dizhi et al.

Quelle: Sensors (14248220); Aug2024, Vol. 24 Issue 16, p5316, 24p

Schlagwörter: CONVOLUTIONAL neural networks, ARTIFICIAL neural networks, DISTRIBUTION (Probability theory), INDUSTRIAL controls manufacturing, CONDITIONAL probability, AUTOENCODERS

Landslide Susceptibility Assessment via Imbalanced Data Augmentation with Tabular Variational Autoencoder and Quality–Diversity Post-Selection.

Autoren: Xu, Zhengyang Wang, Shitai Yin, Min et al.

Quelle: Applied Sciences (2076-3417); Nov2025, Vol. 15 Issue 22, p11965, 25p

Schlagwörter: LANDSLIDES, DATA augmentation, BOOSTING algorithms, NATURAL disasters, RISK assessment

Circular RNA-Drug Association Prediction Based on Multi-Scale Convolutional Neural Networks and Adversarial Autoencoders.

Autoren: Wang, Yao Lei, Xiujuan Chen, Yuli et al.

Quelle: International Journal of Molecular Sciences; Feb2025, Vol. 26 Issue 4, p1509, 20p

Schlagwörter: ARTIFICIAL neural networks, CONVOLUTIONAL neural networks, AUTOENCODERS, CIRCULAR RNA, DRUG target

Short-Term Passenger Flow Forecasting for Rail Transit Inte-Grating Multi-Scale Decomposition and Deep Attention Mechanism.

Autoren: Lu, Youpeng Wang, Jiming

Quelle: Sustainability (2071-1050); Oct2025, Vol. 17 Issue 19, p8880, 21p

DCMF-PPI: a protein-protein interaction predictor based on dynamic condition and multi-feature fusion.

Autoren: Chen, Siqi Zheng, Anhong Yu, Weichi et al.

Quelle: BMC Bioinformatics; 10/15/2025, Vol. 26 Issue 1, p1-27, 27p

Schlagwörter: PROTEIN-protein interactions, DYNAMIC models, CONVOLUTIONAL neural networks, MOLECULAR dynamics, GRAPH neural networks

Frequency-Quantized Variational Autoencoder Based on 2D-FFT for Enhanced Image Reconstruction and Generation.

Autoren: Feng, Jianxin Liu, Xiaoyao

Quelle: Computers, Materials & Continua; 2025, Vol. 83 Issue 2, p2087-2107, 21p

Schlagwörter: IMAGE reconstruction, AUTOENCODERS, PERCEPTUAL learning, FAST Fourier transforms

Enhanced Variational Graph Convolutional Networks with Multi-Scale Convolutions and Attention Mechanisms for Dynamic Network Analysis.

Autoren: Mir, Aabid Ahmad Zuhairi, Megat F. Musa, Shahrulniza et al.

Quelle: Engineering, Technology & Applied Science Research; Feb2025, Vol. 15 Issue 1, p19838-19847, 10p

Schlagwörter: GRAPH neural networks, DEEP learning, CYBERTERRORISM, NEIGHBORHOODS, CLASSIFICATION

WOT-AE: Weighted Optimal Transport Autoencoder for Patterned Fabric Defect Detection.

Autoren: Yang, Hui Kang, Linyan Yang, Tianjin

Quelle: Symmetry (20738994); Nov2025, Vol. 17 Issue 11, p1829, 18p

Schlagwörter: TEXTILES, AUTOENCODERS, MATRIX decomposition, MACHINE learning, SYMMETRY, OUTLIER detection

The ECA‐Informer Algorithm for Diagnosing Motor Bearing Faults Based on Stator Current.

Autoren: Yang, Gang Kang, Haoming Cheng, Lei et al.

Quelle: Journal of Sensors; 10/10/2025, Vol. 2025, p1-18, 18p

Schlagwörter: FAULT diagnosis, FEATURE extraction, STATISTICAL accuracy, ALGORITHMS, ELECTRIC currents, DIAGNOSIS

Unsupervised Convolutional Transformer Autoencoder for Robust Health Indicator Construction and RUL Prediction in Rotating Machinery.

Autoren: Dahal, Amrit Huang, Hong-Zhong Huang, Cheng-Geng et al.

Quelle: Applied Sciences (2076-3417); Oct2025, Vol. 15 Issue 20, p10972, 22p

Schlagwörter: REMAINING useful life, CONVOLUTIONAL neural networks, VIBRATION measurements, MACHINE learning, ENGINEERING systems, TRANSFORMER models, AUTOENCODERS

Learning metal microstructural heterogeneity through spatial mapping of diffraction latent space features.

Autoren: Calvat, Mathieu Bean, Chris Anjaria, Dhruv et al.

Quelle: NPJ Computational Materials; 9/1/2025, Vol. 11 Issue 1, p1-18, 18p

Schlagwörter: METAL microstructure, MACHINE learning, DIMENSIONAL reduction algorithms, MICROSTRUCTURE, THREE-dimensional printing

Efficient Image Compression with Transformer and Convolutional Dual Channel Networks.

Autoren: Jianhua Hu Guixiang Luo Zhangjiang Yuan et al.

Quelle: Journal of Imaging Science & Technology; Jul/Aug2025, Vol. 69 Issue 4, p1-13, 13p

Schlagwörter: IMAGE compression, DEEP learning, CONVOLUTIONAL neural networks, LATENT variables, AUTOENCODERS, TRANSFORMER models

Automated Anomaly Detection in Blast Furnace Shaft Static Pressure Using Adversarial Autoencoders and Mode Decomposition.

Autoren: Sun, Xiaodong Zhu, Jie Tang, Bing et al.

Quelle: Sensors (14248220); Jun2025, Vol. 25 Issue 11, p3473, 17p

Schlagwörter: CLUSTERING algorithms, STATIC pressure, AUTOENCODERS, BLAST furnaces, LABOR costs

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

Unveiling CyberFortis: A Unified Security Framework for IIoT-SCADA Systems with SiamDQN-AE FusionNet and PopHydra Optimizer.

Autoren: Rao, Kuncham Sreenivasa Kotoju, Rajitha Reddy, B. Ramana et al.

Quelle: Computers, Materials & Continua; 2025, Vol. 85 Issue 1, p1899-1916, 18p

Schlagwörter: INTRUSION detection systems (Computer security), SUPERVISORY control & data acquisition systems, REINFORCEMENT learning, DEEP learning, ARTIFICIAL neural networks, CYBERTERRORISM, INTERNET security, AUTOENCODERS

Multiscale neural assimilation scheme for high-resolution sea surface temperature reconstruction from satellite observations.

Autoren: Beauchamp, Maxime Karagali, Ioanna Gacitúa, Guisella et al.

Quelle: Scientific Reports; 11/14/2025, Vol. 15 Issue 1, p1-17, 17p