Suchergebnisse - "Adversarial autoencoder"

Driveshield: Unmasking stealthy attacks on CAN bus via adversarial spatiotemporal feature learning

Autoren: Haoyang Jia Xiaobing Xiong Haibin Luo et al.

Quelle: Journal of King Saud University: Computer and Information Sciences, Vol 37, Iss 9, Pp 1-24 (2025)

Schlagwörter: Controller Area Network (CAN), Intrusion Detection System (IDS), Adversarial Autoencoder, Stealthy Attack Detection, Spatiotemporal Feature Fusion, Electronic computers. Computer science, QA75.5-76.95

Dateibeschreibung: electronic resource

Relation: https://doaj.org/toc/1319-1578; https://doaj.org/toc/2213-1248

Zugangs-URL: https://doaj.org/article/99aef959453541a8b52066f5915eb635

DiffusionAAE: Enhancing hyperspectral image classification with conditional diffusion model and Adversarial Autoencoder

Autoren: Zeyu Cao Jinhui Li Xiangrui Xu

Quelle: Ecological Informatics, Vol 87, Iss , Pp 103118- (2025)

Schlagwörter: Land cover classification, Generative model, Feature extraction, Hyperspectral image classification, Conditional diffusion model, Adversarial autoencoder, Information technology, T58.5-58.64, Ecology, QH540-549.5

Dateibeschreibung: electronic resource

Relation: http://www.sciencedirect.com/science/article/pii/S157495412500127X; https://doaj.org/toc/1574-9541

Zugangs-URL: https://doaj.org/article/ad41b692c5984e31b024c955e44b6c99

Improving trust and confidence in medical skin lesion diagnosis through explainable deep learning

Autoren: Metta, Carlo Beretta, Andrea Guidotti, Riccardo et al.

Weitere Verfasser: Metta, Carlo Beretta, Andrea Guidotti, Riccardo et al.

Schlagwörter: Adversarial autoencoder, dermoscopic image, explainable artificial intelligence, skin image analysi, artificial-intelligence, black-box, Settore INF/01 - Informatica

Relation: info:eu-repo/semantics/altIdentifier/wos/WOS:001013805500001; volume:20; firstpage:183; numberofpages:13; journal:INTERNATIONAL JOURNAL OF DATA SCIENCE AND ANALYTICS; https://hdl.handle.net/11384/137124

Verfügbarkeit: https://hdl.handle.net/11384/137124
https://doi.org/10.1007/s41060-023-00401-z

Anomalous Radio Signal Detection Based on an Adversarial Autoencoder

Autoren: Huan Wang Yushu Luo Fan Long et al.

Quelle: Electronics ; Volume 14 ; Issue 9 ; Pages: 1785

Schlagwörter: anomalous radio signal detection, generative adversarial network, adversarial autoencoder, time–frequency features, unsupervised learning

Dateibeschreibung: application/pdf

Relation: https://dx.doi.org/10.3390/electronics14091785

Verfügbarkeit: https://doi.org/10.3390/electronics14091785

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

Autoren: Yao Wang Xiujuan Lei Yuli Chen et al.

Quelle: International Journal of Molecular Sciences ; Volume 26 ; Issue 4 ; Pages: 1509

Schlagwörter: circular RNA-drug association prediction, multi-scale convolutional neural network, adversarial autoencoder

Geographisches Schlagwort: agris

Dateibeschreibung: application/pdf

Relation: Molecular Informatics; https://dx.doi.org/10.3390/ijms26041509

Verfügbarkeit: https://doi.org/10.3390/ijms26041509

Retrospective respiratory motion correction in cardiac cine MRI reconstruction using adversarial autoencoder and unsupervised learning

Autoren: Ghodrati, Vahid Bydder, Mark Ali, Fadil et al.

Quelle: NMR in Biomedicine. 34(2)

Schlagwörter: Biomedical and Clinical Sciences, Clinical Sciences, Biomedical Imaging, Clinical Research, Artifacts, Breath Holding, Computer Simulation, Heart, Humans, Image Processing, Computer-Assisted, Magnetic Resonance Imaging, Cine, Motion, Neural Networks, Computer, Respiration, Statistics, Nonparametric, Unsupervised Machine Learning, adversarial autoencoder, cardiovascular magnetic resonance, deep learning, magnetic resonance imaging, respiratory motion correction, adversarial autoencoder, cardiovascular magnetic resonance, deep learning, magnetic resonance imaging, respiratory motion correction, Medicinal and Biomolecular Chemistry, Biomedical Engineering, Nuclear Medicine & Medical Imaging, Clinical sciences, Biomedical engineering

Dateibeschreibung: application/pdf

Zugangs-URL: https://escholarship.org/uc/item/8k99s5qj
https://escholarship.org/content/qt8k99s5qj/qt8k99s5qj.pdf

Single-cell RNA-Seq Clustering Based on Dual Autoencoder with Variational Bayes

Autoren: JIA Jihua XU Yaokui WANG Minghui

Quelle: Journal of Harbin University of Science and Technology, Vol 29, Iss 03, Pp 125-133 (2024)

Schlagwörter: single-cell rna sequencing, adversarial autoencoder, autoencoder network, variational bayes, cell clustering, Technology, Science

Dateibeschreibung: electronic resource

Relation: https://hlgxb.hrbust.edu.cn/#/digest?ArticleID=2339; https://doaj.org/toc/1007-2683

Zugangs-URL: https://doaj.org/article/778a9e6dd5c34164acba336f3272be5a

Addressing Credit Card Fraud Detection Challenges with Adversarial Autoencoders

Autoren: Shiyu Ma Carol Anne Hargreaves

Quelle: Big Data and Cognitive Computing, Vol 9, Iss 7, p 168 (2025)

Schlagwörter: credit card, fraud detection, adversarial autoencoder, Shapley values, deep learning, risk, Technology

Dateibeschreibung: electronic resource

Relation: https://www.mdpi.com/2504-2289/9/7/168; https://doaj.org/toc/2504-2289

Zugangs-URL: https://doaj.org/article/829c7013e1fc4374a760c36d738c55c2

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

Autoren: Yanru Chen Bei Wu Wang Zhong et al.

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

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

Dateibeschreibung: electronic resource

Relation: https://www.mdpi.com/1424-8220/25/10/3249; https://doaj.org/toc/1424-8220

Zugangs-URL: https://doaj.org/article/19daf4992a324d7b9031944823d468f2

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

Autoren: Xiaodong Sun Jie Zhu Bing Tang et al.

Quelle: Sensors, Vol 25, Iss 11, p 3473 (2025)

Schlagwörter: blast furnace monitoring, time-series anomaly detection, adversarial autoencoder, variational mode decomposition, unsupervised learning, Chemical technology, TP1-1185

Dateibeschreibung: electronic resource

Relation: https://www.mdpi.com/1424-8220/25/11/3473; https://doaj.org/toc/1424-8220

Zugangs-URL: https://doaj.org/article/3c80ec210c5e44ddb936c6dedd8ad0a4

Purifying Adversarial Images Using Adversarial Autoencoder With Conditional Normalizing Flows

Autoren: Yi Ji Trung-Nghia Le Huy H. Nguyen et al.

Quelle: IEEE Open Journal of Signal Processing, Vol 4, Pp 267-274 (2023)

Schlagwörter: representation learning, Adversarial autoencoder, adversarial purification, normalizing flow, Electrical engineering. Electronics. Nuclear engineering, TK1-9971

Zugangs-URL: https://doaj.org/article/8d88827daf114ca2aa12aa7bc8891903

A Feature Mapping Technique for Complex Data Object Generation With Likelihood and Deep Generative Approaches

Autoren: Shashika R. Muramudalige Anura P. Jayasumana Haonan Wang

Quelle: IEEE Access, Vol 11, Pp 136643-136653 (2023)

Schlagwörter: synthetic data generation, copulas, Adversarial autoencoder, Electrical engineering. Electronics. Nuclear engineering, generative adversarial networks, TK1-9971

Zugangs-URL: https://doaj.org/article/37975c346e944829b54ab17f07c04073

FMNet: Latent Feature-Wise Mapping Network for Cleaning Up Noisy Micro-Doppler Spectrogram

Autoren: Chong Tang Wenda Li Shelly Vishwakarma et al.

Quelle: IEEE Transactions on Geoscience and Remote Sensing. 60:1-12

Schlagwörter: Signal Processing (eess.SP), FOS: Computer and information sciences, Computer Science - Machine Learning, Activity Classification, Feature Mapping, 02 engineering and technology, Activity classification, Machine Learning (cs.LG), Variational Autoencoder, deep learning (DL), Deep Learning, passive WiFi radar (PWR), feature mapping, micro-Doppler spectrogram (μ-DS), FOS: Electrical engineering, electronic engineering, information engineering, 0202 electrical engineering, electronic engineering, information engineering, adversarial autoencoder (AAE), variational autoencoder (VAE), Electrical Engineering and Systems Science - Signal Processing, Micro-Doppler Spectrogram, Adversarial Autoencoder, Passive WiFi Radar

Dateibeschreibung: application/pdf

Zugangs-URL: http://arxiv.org/pdf/2107.07312
http://arxiv.org/abs/2107.07312
https://ieeexplore.ieee.org/document/9583945
https://dblp.uni-trier.de/db/journals/corr/corr2107.html#abs-2107-07312
https://www.arxiv-vanity.com/papers/2107.07312/
https://discovery-pp.ucl.ac.uk/id/eprint/10136070/

Deep Learning-Based Probabilistic Autoencoder for Residential Energy Disaggregation: An Adversarial Approach

Autoren: Halil Cimen Ying Wu Yanpeng Wu et al.

Quelle: Cimen, H, Wu, Y, Wu, Y, Terriche, Y, Vasquez, J C & Guerrero, J M 2022, 'Deep Learning-based Probabilistic Autoencoder for Residential Energy Disaggregation : An Adversarial Approach', IEEE Transactions on Industrial Informatics, vol. 18, no. 12, pp. 8399-8408. https://doi.org/10.1109/TII.2022.3150334

Schlagwörter: Generative adversarial networks, Adversarial autoencoder, Energy disaggregation, Probabilistic energy disaggregation, Nonintrusive load monitoring (NILM), 0202 electrical engineering, electronic engineering, information engineering, Deep learning, 02 engineering and technology, Residential energy disaggregation, 7. Clean energy, Online energy disaggregation

Zugangs-URL: http://www.scopus.com/inward/record.url?scp=85124765333&partnerID=8YFLogxK
https://vbn.aau.dk/da/publications/1afe3cda-3abf-4394-aa8f-671c9b4b2f76
https://doi.org/10.1109/TII.2022.3150334

AAEGAN Loss Optimizations Supporting Data Augmentation on Cerebral Organoid Bright-field Images

Autoren: Brémond Martin, Clara Chane, Camille Clouchoux, Cedric et al.

Weitere Verfasser: Brémond Martin, Clara Chane, Camille Clouchoux, Cedric et al.

Quelle: Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications. :307-314

Schlagwörter: 0301 basic medicine, Adversarial Autoencoder (AAE), 03 medical and health sciences, Segmentation, 0302 clinical medicine, [INFO.INFO-TI] Computer Science [cs]/Image Processing [eess.IV], Generation, Loss, Cerebral Organoid, t-SNE, [SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing

Zugangs-URL: https://hal.science/hal-03528008v1

DP-VAE: Human-Readable Text Anonymization for Online Reviews with Differentially Private Variational Autoencoders

Autoren: Weggenmann, Benjamin Rublack, Valentin Andrejczuk, Michael et al.

Quelle: Proceedings of the ACM Web Conference 2022. :721-731

Schlagwörter: adversarial autoencoder, authorship obfuscation, disentangled representations, authorship attribution, differential privacy, 0202 electrical engineering, electronic engineering, information engineering, variational autoencoder, 02 engineering and technology, online reviews, text anonymization

scSemiAAE: a semi-supervised clustering model for single-cell RNA-seq data

Autoren: Zile Wang Haiyun Wang Jianping Zhao et al.

Quelle: BMC Bioinformatics, Vol 24, Iss 1, Pp 1-17 (2023)

Schlagwörter: Deep learning, scRNA-seq, Semi-supervised, Clustering, Adversarial autoencoder, Computer applications to medicine. Medical informatics, R858-859.7, Biology (General), QH301-705.5

Dateibeschreibung: electronic resource

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

Zugangs-URL: https://doaj.org/article/2802398c8a174a83a1a49471719571cf

Self-Supervised Learning Based Anomaly Detection in Synthetic Aperture Radar Imaging

Autoren: Max Muzeau Chengfang Ren Sebastien Angelliaume et al.

Quelle: IEEE Open Journal of Signal Processing, Vol 3, Pp 440-449 (2022)

Schlagwörter: Adversarial autoencoder, self-supervised, 4. Education, 0211 other engineering and technologies, 0202 electrical engineering, electronic engineering, information engineering, Electrical engineering. Electronics. Nuclear engineering, 02 engineering and technology, deep-learning, anomaly detection, despeckling, SAR, TK1-9971

Zugangs-URL: https://doaj.org/article/251175771b14449b9366483032682a76

Learning to Generate SAR Images With Adversarial Autoencoder

Autoren: Qian Song Feng Xu Xiao Xiang Zhu et al.

Quelle: IEEE Transactions on Geoscience and Remote Sensing. 60:1-15

Schlagwörter: Synthetic Aperture Radar (SAR), Deep Learning, Image Representation, 0211 other engineering and technologies, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology, Few-shot Learning (FSL), Adversarial Autoencoder

Zugangs-URL: https://elib.dlr.de/142830/1/Learning_to_Generate_SAR_Images_With_Adversarial_Autoencoder.pdf
https://ieeexplore.ieee.org/document/9461232

Latent Space Representation of Human Movement: Assessing the Effects of Fatigue

Autoren: Thomas Rousseau Gentiane Venture Vincent Hernandez

Quelle: Sensors, Vol 24, Iss 23, p 7775 (2024)

Schlagwörter: fatigue, human activity recognition, deep learning, adversarial autoencoder, inertial measurement unit, ground reaction force, Chemical technology, TP1-1185

Dateibeschreibung: electronic resource

Relation: https://www.mdpi.com/1424-8220/24/23/7775; https://doaj.org/toc/1424-8220

Zugangs-URL: https://doaj.org/article/3b055c2ead664cdfb9fc9c8dfc053880