Výsledky vyhledávání - Autoencoder Framework*

A supervised variational autoencoder framework for dimensionality reduction and predictive modeling in high-dimensional socioeconomic data

Autoři: Pei Xue Tianshun Li

Zdroj: Journal of Economy and Technology, Vol 4, Iss, Pp 9-19 (2026)

Témata: High-dimensional data, Socioeconomic forecasting, Economics as a science, Electronic computers. Computer science, Supervised variational autoencoder, Social Sciences, QA75.5-76.95, Dimensionality reduction, HB71-74, Nonlinear representation learning, Predictive modeling

Přístupová URL adresa: https://doaj.org/article/38a6a8d09a8045ceaf6f58f757d3bf5e

Enhanced Adaptive Autoencoder Framework for Continuous Monitoring and Fault Management in Industrial Sensors

Autoři: Lincoln Moura de Oliveira Menaouar Berrehil El Kattel Demercil de Souza Oliveira a další

Zdroj: Oliveira, L M D, Kattel, M B E, Oliveira, D D S, Vasquez, J C, Guerrero, J M & Antunes, F L M 2025, 'Enhanced Adaptive Autoencoder Framework for Continuous Monitoring and Fault Management in Industrial Sensors', IEEE Sensors Journal, vol. 25, no. 13, pp. 25682-25692. https://doi.org/10.1109/JSEN.2025.3565982

Témata: autoencoder (AE), sensor fault diagnosis and isolation, Autoencoder (AE), Industrial process monitoring, industrial process monitoring, name=SDG 11 - Sustainable Cities and Communities

A Novel Latent Space Data Assimilation Framework with Autoencoder-Observation to Latent Space (AE-O2L) Network. Part II: Observation and Background Assimilation with Interpretability

Autoři: Hang Fan Yubao Liu Yuewei Liu a další

Zdroj: Monthly Weather Review. 153:1349-1363

Adaptive hybrid convolutional neural network-autoencoder framework for backdoor detection in GenAI-driven semantic communication systems

Autoři: Hassan El Alami Danda B. Rawat

Zdroj: ITU Journal on Future and Evolving Technologies. 6:309-321

A Novel Latent Space Data Assimilation Framework with Autoencoder-Observation to Latent Space (AE-O2L) Network. Part I: The Observation-Only Analysis Method

Autoři: Hang Fan Yubao Liu Zhaoyang Huo a další

Zdroj: Monthly Weather Review. 153:1335-1348

A Novel Framework for Predicting Phage-Host Interactions via Host Specificity-Aware Graph Autoencoder

Autoři: Zhen Xiao Han Sun Ankang Wei a další

Zdroj: IEEE Journal of Biomedical and Health Informatics. 29:3069-3078

Témata: Bacteria, Host-Pathogen Interactions, Computational Biology, Humans, Bacteriophages, Autoencoder, Host Specificity, Algorithms

Přístupová URL adresa: https://pubmed.ncbi.nlm.nih.gov/40030240

Hybrid Outlier Detection Framework Based on Optimized KMeans and HDBSCAN Using Bat Algorithm and LSTM Autoencoder

Autoři: Mai Abdelsamie Hosam Refaat Mohammed Abdallah a další

Zdroj: Statistics, Optimization & Information Computing. 14:970-1017

Head-Related Transfer Function Upsampling Using an Autoencoder-Based Generative Adversarial Network With Evaluation Framework

Autoři: Hu, Xuyi Li, Jian Picinali, Lorenzo a další

Přispěvatelé: Hu, Xuyi Li, Jian Picinali, Lorenzo a další

Zdroj: Journal of the Audio Engineering Society. 73:533-547

Témata: 4006 Communications Engineering

Popis souboru: application/pdf

ESAE-SDA: ensemble sparse autoencoder framework for epigenomics-informed snoRNA-disease associations prediction

Autoři: Xinqing Jiang Xiaojun Chen Lifeng Xu a další

Zdroj: BMC Bioinformatics, Vol 26, Iss 1, Pp 1-18 (2025)

Témata: Epigenomics, snoRNA-disease associations (SDAs), Ensemble learning framework, Sparse autoencoder, Dynamically sampling, Artificial intelligence (AI), Computer applications to medicine. Medical informatics, R858-859.7, Biology (General), QH301-705.5

Popis souboru: electronic resource

Relation: https://doaj.org/toc/1471-2105

Přístupová URL adresa: https://doaj.org/article/4a1813752009454491f25e2b31390236

Intelligent guidance system for the visually impaired person using a lightweight YOLOv4-based object detection and sparse autoencoder framework

Autoři: Alaa O. Khadidos Ayman Yafoz

Zdroj: Journal of the Chinese Institute of Engineers. :1-21

Development of Adversaries Detection Framework using Ensemble of Residual Autoencoders with Attention Mechanism in Wireless Body Area Networks

Autoři: R. N. L. S. Kalpana Ajit Kumar Patro D. Nageshwar Rao

Zdroj: 2025 5th International Conference on Soft Computing for Security Applications (ICSCSA). :130-138

Optimized Video Streaming in Mobile Environments: A Novel Multihead Autoencoder and Red-Tailed Hawk Optimization Framework

Autoři: Duraimurugan Samiayya Chinnasamy Ambayiram Hariprasad Natarajan a další

Zdroj: IETE Journal of Research. :1-13

Edge based Autoencoder XGBoost Framework to Enhance IoT Security Against DoS Attack

Autoři: P. Sivakumar Jeyaselvi M

Zdroj: 2025 8th International Conference on Computing Methodologies and Communication (ICCMC). :424-429

MuAE: A Mutation Testing Framework for Evaluating Autoencoders

Autoři: Samer Y. Khamaiseh Steven Chiacchira Anas Alsobeh a další

Zdroj: 2025 IEEE 49th Annual Computers, Software, and Applications Conference (COMPSAC). :1015-1020

ContraMAE: Contrastive alignment masked autoencoder framework for cancer survival prediction: Contrastive alignment masked autoencoder framework for cancer survival prediction

Autoři: Wang, Suixue Lai, Huiyuan Wang, Shuling a další

Zdroj: 2024 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). :2621-2626

Témata: Pathology-genomics Alignment, Survival prediction, Multimodal pre-training, Masked autoencoder, Contrastive learning

Přístupová URL adresa: https://research.rug.nl/en/publications/1fd5b6ea-8360-4603-aad7-47cf199b207d
https://hdl.handle.net/11370/1fd5b6ea-8360-4603-aad7-47cf199b207d
https://doi.org/10.1109/BIBM62325.2024.10821720

SSL-MAE: Adaptive Semisupervised Learning Framework for Multilabel Classification of Remote Sensing Images Using Masked Autoencoders

Autoři: Marjan Stoimchev Jurica Levatić Dragi Kocev a další

Zdroj: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 18, Pp 14882-14896 (2025)

Témata: Ocean engineering, QC801-809, self-supervised learning, Geophysics. Cosmic physics, multilabel classification (MLC), Masked autoencoders (MAEs), remote sensing images, semisupervised learning (SSL), TC1501-1800

Přístupová URL adresa: https://doaj.org/article/b23c928fc51142a8bda63dd596895554

A Hybrid Machine Learning-Based Framework for Data Injection Attack Detection in Smart Grids Using PCA and Stacked Autoencoders

Autoři: Shahid Tufail Hasan Iqbal Mohd Tariq a další

Zdroj: IEEE Access, Vol 13, Pp 33783-33798 (2025)

Témata: multi-layer perceptron (MLP), machine learning algorithms, autoencoders, grid-connected PV systems, Electrical engineering. Electronics. Nuclear engineering, Photovoltaic (PV) systems, random forest, TK1-9971

Přístupová URL adresa: https://doaj.org/article/ae0ba93fe9954d4ead939ac8b5b9f52f

SecMa: A Novel Multimodal Autoencoder Framework for Encrypted IoT Traffic Analysis and Attack Detection

Autoři: V. Ravi A. S. Poornima

Zdroj: Engineering, Technology & Applied Science Research. 15:23020-23026

MinGRU-Based Encoder for Turbo Autoencoder Frameworks

Autoři: Fritschek, Rick Schaefer, Rafael F.

Zdroj: 2025 IEEE International Conference on Machine Learning for Communication and Networking (ICMLCN). :1-6

Témata: FOS: Computer and information sciences, Computer Science - Machine Learning, Computer Science - Information Theory, Information Theory (cs.IT), Machine Learning (cs.LG)

Přístupová URL adresa: http://arxiv.org/abs/2503.08451

Beyond Labels: A Self-Supervised Framework with Masked Autoencoders and Random Cropping for Breast Cancer Sub-type Classification

Autoři: Chiocchetti, Annalisa Dossena, Marco Irwin, Christopher a další

Zdroj: Proceedings of the AAAI Symposium Series. 5:10-17

Témata: FOS: Computer and information sciences, Computer Science - Machine Learning, Artificial Intelligence (cs.AI), Computer Science - Artificial Intelligence, Computer Vision and Pattern Recognition (cs.CV), Computer Science - Computer Vision and Pattern Recognition, Machine Learning (cs.LG)

Přístupová URL adresa: http://arxiv.org/abs/2410.12006