Výsledky vyhledávání - boosting adversarial autoencoder*

DBN-BAAE: Enhanced Lightweight Anomaly Detection Mechanism with Boosting Adversarial Autoencoder

Autoři: Yanru Chen Bei Wu Wang Zhong a další

Zdroj: Sensors (Basel)
Sensors, Vol 25, Iss 10, p 3249 (2025)

Témata: deep belief network, industrial control systems, dynamic threshold, Chemical technology, boosting adversarial autoencoder, TP1-1185, anomaly detection, Article

Přístupová URL adresa: https://doaj.org/article/19daf4992a324d7b9031944823d468f2

DBN-BAAE: Enhanced Lightweight Anomaly Detection Mechanism with Boosting Adversarial Autoencoder.

Autoři: Chen, Yanru Wu, Bei Zhong, Wang a další

Zdroj: Sensors (14248220); May2025, Vol. 25 Issue 10, p3249, 21p

Témata: ENSEMBLE learning, ANOMALY detection (Computer security), INDUSTRIAL controls manufacturing, AUTOENCODERS, DIGITAL technology

An enhanced ensemble defense framework for boosting adversarial robustness of intrusion detection systems

Autoři: Zeinab Awad Magdy Zakaria Rasha Hassan

Zdroj: Scientific Reports, Vol 15, Iss 1, Pp 1-23 (2025)

Témata: Machine learning, Intrusion detection systems, Adversarial attacks, Adversarial defense, Deep learning, Ensemble learning, Medicine, Science

Popis souboru: electronic resource

Relation: https://doaj.org/toc/2045-2322

Přístupová URL adresa: https://doaj.org/article/874ac489578144b8b7d681eb09ee3db8

Poster: Boosting Adversarial Robustness by Adversarial Pre-training

Autoři: Xiaoyun Xu Stjepan Picek Meng, W.

Přispěvatelé: Xiaoyun Xu Stjepan Picek Meng, W.

Zdroj: Meng, W. (ed.), CCS '23: ACM SIGSAC Conference on Computer and Communications Security Copenhagen Denmark November 26-30, 2023, pp. 3540-3542

Témata: vision transformers, adversarial training, Digital Security

Přístupová URL adresa: https://hdl.handle.net/2066/299149
https://repository.ubn.ru.nl//bitstream/handle/2066/299149/299149.pdf

Kruskal Szekeres generative adversarial network augmented deep autoencoder for colorectal cancer detection

Autoři: Suresh Kumar, Krishnamoorthy Vanitha Cn

Zdroj: Network: Computation in Neural Systems. :1-27

Přístupová URL adresa: https://pubmed.ncbi.nlm.nih.gov/39550608

An Optimized Transformer–GAN–AE for Intrusion Detection in Edge and IIoT Systems: Experimental Insights from WUSTL-IIoT-2021, EdgeIIoTset, and TON_IoT Datasets.

Autoři: Salehiyan, Ahmad Moghaddam, Pardis Sadatian Kaveh, Masoud

Zdroj: Future Internet. Jul2025, Vol. 17 Issue 7, p279. 34p.

Témata: Intrusion detection systems (Computer security), Edge computing, Autoencoder, Internet security, Cyber physical systems, Deep learning, Generative adversarial networks

Data augmentation for time series regression: Applying transformations, autoencoders and adversarial networks to electricity price forecasting

Autoři: Demir, Sumeyra Mincev, Krystof Kok, Koen a další

Zdroj: Applied Energy vol.304 (2021) date: 2021-12-15 [ISSN 0306-2619]

Témata: Adversarial network, Augmentation, Autoencoder, Electricity price forecasting, Multivariate time series, Regression, Tijdschriftartikel, Article

URL: https://research.tue.nl/en/publications/d9c5eb14-3cf5-4f0c-b91e-6f09facc0acb
https://pure.tue.nl/ws/files/187920059/1_s2.0_S0306261921010527_main.pdf
https://pure.tue.nl/ws/files/187920059/1_s2.0_S0306261921010527_main.pdf

Bringing realism: Enhancing high-dimensional data for active behavior analysis in older adults.

Autoři: Guo, Cong Jiang, Yaoqin Yang, Yitong a další

Zdroj: Journal of Transport Geography. Dec2025, Vol. 129, pN.PAG-N.PAG. 1p.

Témata: GENERATIVE adversarial networks, DATA modeling, PHYSICAL mobility, LATENT variables, BOOSTING algorithms, OLDER people

Geografický termín: XIAMEN Shi (China), CHINA

Unified multi-protocol MRI for Alzheimer's disease diagnosis: Dual-decoder adversarial autoencoder and ensemble residual shrinkage attention network.

Autoři: Li, Shiyao Lin, Shukuan Tu, Yue a další

Zdroj: Biomedical Signal Processing & Control. Jul2025, Vol. 105, pN.PAG-N.PAG. 1p.

Témata: Computer-aided diagnosis, Three-dimensional imaging, Alzheimer's disease, Magnetic resonance imaging, Mild cognitive impairment

MDGAN: Boosting Anomaly Detection Using \\Multi-Discriminator Generative Adversarial Networks

Autoři: Intrator, Yotam Katz, Gilad Shabtai, Asaf

Témata: Computer Science - Machine Learning, Statistics - Machine Learning, text

URL: http://arxiv.org/abs/1810.05221

LLM-AE-MP: Web Attack Detection Using a Large Language Model with Autoencoder and Multilayer Perceptron.

Autoři: Yang, Jing Wu, Yuangui Yuan, Yuping a další

Zdroj: Expert Systems with Applications. May2025, Vol. 274, pN.PAG-N.PAG. 1p.

Témata: *LONG short-term memory, *GENERATIVE adversarial networks, *LANGUAGE models, *AUTOENCODERS, *WEB-based user interfaces

Universal Adversarial Training Using Auxiliary Conditional Generative Model-Based Adversarial Attack Generation.

Autoři: Dingeto, Hiskias Kim, Juntae

Zdroj: Applied Sciences (2076-3417); Aug2023, Vol. 13 Issue 15, p8830, 17p

Témata: MACHINE learning, GENERATIVE adversarial networks, DATA augmentation, BOOSTING algorithms

Data augmentation for time series regression:Applying transformations, autoencoders and adversarial networks to electricity price forecasting

Autoři: Demir, Sumeyra Mincev, Krystof Kok, Koen a další

Zdroj: Demir, S, Mincev, K, Kok, K & Paterakis, N G 2021, 'Data augmentation for time series regression : Applying transformations, autoencoders and adversarial networks to electricity price forecasting', Applied Energy, vol. 304, 117695. https://doi.org/10.1016/j.apenergy.2021.117695

Témata: Adversarial network, Augmentation, Autoencoder, Electricity price forecasting, Multivariate time series, Regression

Popis souboru: application/pdf

Relation: info:eu-repo/semantics/altIdentifier/pissn/0306-2619

Dostupnost: https://research.tue.nl/en/publications/d9c5eb14-3cf5-4f0c-b91e-6f09facc0acb
https://doi.org/10.1016/j.apenergy.2021.117695
https://pure.tue.nl/ws/files/187920059/1_s2.0_S0306261921010527_main.pdf
https://www.scopus.com/pages/publications/85114608882

Boosting adversarial robustness via feature refinement, suppression, and alignment.

Autoři: Wu, Yulun Guo, Yanming Chen, Dongmei a další

Zdroj: Complex & Intelligent Systems; Jun2024, Vol. 10 Issue 3, p3213-3233, 21p

Témata: ARTIFICIAL neural networks, RSA algorithm

Towards effective and robust bank fraud detection thanks to machine learning.

Autoři: Cedric, Cheun Anthony Ould-Slimane, Hakima

Zdroj: Procedia Computer Science. 2025, Vol. 265, p25-32. 8p.

Témata: Credit card fraud, Machine learning, Boosting algorithms, Metadata, Distribution (Probability theory), Bank fraud, Random forest algorithms

A Hybrid Deep Learning Model for E‐Commerce Recommendations: Sentiment Analysis With Autoencoders and Generative Adversarial Networks.

Autoři: Yarjanli, Mohammad Mahdinasab, Neda Murray, Richard

Zdroj: International Journal of Intelligent Systems; 10/2/2025, Vol. 2025, p1-36, 36p

Témata: SENTIMENT analysis, DEEP learning, GENERATIVE adversarial networks, FEATURE extraction, ELECTRONIC commerce, AUTOENCODERS

Ranking-enhanced anomaly detection using Active Learning-assisted Attention Adversarial Dual AutoEncoder.

Autoři: Benabderrahmane, Sidahmed Cheney, James Rahwan, Talal

Zdroj: Scientific Reports; 11/24/2025, Vol. 15 Issue 1, p1-42, 42p

Témata: ANOMALY detection (Computer security), ACTIVE learning, AUTOENCODERS, INFORMATION asymmetry, INTERNET security

Addressing Credit Card Fraud Detection Challenges with Adversarial Autoencoders.

Autoři: Ma, Shiyu Hargreaves, Carol Anne

Zdroj: Big Data & Cognitive Computing; Jul2025, Vol. 9 Issue 7, p168, 14p

Témata: CREDIT card fraud, GENERATIVE adversarial networks, FRAUD, FINANCIAL services industry, MACHINE learning

Boosting Transferability of Adversarial Examples with Spatio-Temporal Context.

Autoři: Wang, Jingtian Li, Xiaolong Ma, Bin a další

Zdroj: ACM Transactions on Multimedia Computing, Communications & Applications; Oct2025, Vol. 21 Issue 10, p1-22, 22p

Témata: SUCCESS

SAE-GAN: integrating stacked attention autoencoder and generative adversarial networks for multivariate time series anomaly detection.

Autoři: Sun, Shimin Liu, Xiangyun Han, Li a další

Zdroj: Applied Intelligence; Nov2025, Vol. 55 Issue 16, p1-18, 18p