Výsledky vyhledávání - Deep-stacked denoising autoencoder

Deep stacked denoising autoencoder for unsupervised anomaly detection in video surveillance

Autoři: Sanjay Roka Manoj Diwakar

Zdroj: Journal of Electronic Imaging. 32

Deep learning framework designed for high-performance lithium-ion batteries state monitoring

Autoři: Paul Takyi-Aninakwa Shunli Wang Guangchen Liu a další

Zdroj: Renewable and Sustainable Energy Reviews. 218:115803

Témata: Lithium-ion batteries, State of charge estimation, Secondary scale feature extraction, Long short-term memory, Deep-stacked denoising autoencoder

Přístupová URL adresa: https://rgu-repository.worktribe.com/output/2830428

A selective deep stacked denoising autoencoders ensemble with negative correlation learning for gearbox fault diagnosis.

Autoři: Yu, Jianbo¹ jianboyu.bob@gmail.com

Zdroj: Computers in Industry. Jun2019, Vol. 108, p62-72. 11p.

Témata: *STATISTICAL correlation, DEEP learning, SIGNAL denoising, DEBUGGING, GEARBOXES

Denoising x-vectors for Robust Speaker Recognition

Autoři: Mohammadamini, Mohammad Matrouf, Driss Noé, Paul-Gauthier

Přispěvatelé: Mohammadamini, Mohammad Matrouf, Driss Noé, Paul-Gauthier

Zdroj: The Speaker and Language Recognition Workshop (Odyssey 2020). :75-80

Témata: x-vector, 03 medical and health sciences, Noise compensation, Key terms: Speaker recognition, i-MAP, 0202 electrical engineering, electronic engineering, information engineering, Denoising autoencoder, 02 engineering and technology, [INFO] Computer Science [cs], 0305 other medical science

Popis souboru: application/pdf

Přístupová URL adresa: https://hal.archives-ouvertes.fr/hal-02614616/file/78%20%281%29.pdf
https://hal.science/hal-02614616v1/document
https://doi.org/10.21437/odyssey.2020-11
https://hal.science/hal-02614616v1
https://hal.archives-ouvertes.fr/hal-02614616/document
https://hal.archives-ouvertes.fr/hal-02614616
https://dblp.uni-trier.de/db/conf/odyssey/odyssey2020.html#MohammadAminiMN20

Detecting network intrusions in cyber-physical systems using deep autoencoder-based dimensionality reduction approach and deep neural networks.

Autoři: Ibor, A. E. Egete, D. O. Otiko, A. O. a další

Zdroj: Journal of Nigerian Society of Physical Sciences; Aug2025, Vol. 7 Issue 3, p1-15, 15p

Témata: ARTIFICIAL neural networks, FEEDFORWARD neural networks, AUTOENCODERS, CYBER physical systems, COMPUTER network traffic, DEEP learning

Data augmentation versus noise compensation for x- vector speaker recognition systems in noisy environments

Autoři: Mohammadamini, Mohammad Matrouf, Driss Laboratoire Informatique d'Avignon (LIA) a další

Přispěvatelé: Mohammadamini, Mohammad Matrouf, Driss Laboratoire Informatique d'Avignon (LIA) a další

Zdroj: EUSIPCO ; https://hal.science/hal-02882342 ; EUSIPCO, Jan 2021, Amsterdam, Netherlands

Témata: speaker recognition, x-vector, data augmentation, noise compensation, denoising autoencoder, deep stacked denoising autoencoder, [INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL], [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]

Geografické téma: Amsterdam, Netherlands

Relation: info:eu-repo/semantics/altIdentifier/arxiv/2006.15903; ARXIV: 2006.15903

Dostupnost: https://hal.science/hal-02882342
https://hal.science/hal-02882342v1/document
https://hal.science/hal-02882342v1/file/Data%20augmentation%20versus%20noise%20compensation%20for%20xvector%20speaker%20recognition%20systems%20in%20noisy.pdf

A novel stacked sparse denoising autoencoder for mammography restoration to visual interpretation of breast lesion

Autoři: Swarup Kr Ghosh Biswajit Biswas Anupam Ghosh

Zdroj: Evolutionary Intelligence. 14:133-149

Témata: 03 medical and health sciences, 0302 clinical medicine, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Data augmentation versus noise compensation for x- vector speaker recognition systems in noisy environments

Autoři: Mohammadamini, Mohammad Matrouf, Driss

Přispěvatelé: Mohammadamini, Mohammad Matrouf, Driss

Témata: [INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI], FOS: Computer and information sciences, Sound (cs.SD), Computer Science - Computation and Language, deep stacked denoising autoencoder, speaker recognition, 02 engineering and technology, Computer Science - Sound, x-vector, noise compensation, [INFO.INFO-CL] Computer Science [cs]/Computation and Language [cs.CL], Audio and Speech Processing (eess.AS), denoising autoencoder, 0202 electrical engineering, electronic engineering, information engineering, FOS: Electrical engineering, electronic engineering, information engineering, Computation and Language (cs.CL), data augmentation, Electrical Engineering and Systems Science - Audio and Speech Processing

Popis souboru: application/pdf

Přístupová URL adresa: http://arxiv.org/abs/2006.15903
https://hal.science/hal-02882342v1
https://hal.science/hal-02882342v1/document

Deep stacked denoising autoencoder for unsupervised anomaly detection in video surveillance.

Autoři: Roka, Sanjay Diwakar, Manoj

Zdroj: Journal of Electronic Imaging; May/Jun2023, Vol. 32 Issue 3, p33015-033015-23, 1p

Témata: VIDEO surveillance, ANOMALY detection (Computer security), IMAGE denoising, OPTICAL flow, CONVOLUTIONAL neural networks, DEEP learning

Reconstructing echoes completely submerged in background noise by a stacked denoising autoencoder method for low-power EMAT testing

Autoři: Jinjie Zhou Dianrui Yu Xiang Li a další

Zdroj: Measurement Science and Technology. 34:125910

Témata: 0103 physical sciences, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology, 01 natural sciences

A novel stacked sparse denoising autoencoder for mammography restoration to visual interpretation of breast lesion.

Autoři: Ghosh, Swarup Kr Biswas, Biswajit Ghosh, Anupam

Zdroj: Evolutionary Intelligence; Mar2021, Vol. 14 Issue 1, p133-149, 17p

Monitoring of complex profiles based on deep stacked denoising autoencoders.

Autoři: Chen, Shumei Yu, Jianbo Wang, Shijin

Zdroj: Computers & Industrial Engineering. May2020, Vol. 143, pN.PAG-N.PAG. 1p.

Témata: *STATISTICAL process control, VISUAL learning, DEEP learning, ACOUSTIC field, FALSE alarms, AUTOCORRELATION (Statistics)

Ground Target Recognition Using Carrier-Free UWB Radar Sensor With a Semi-Supervised Stacked Convolutional Denoising Autoencoder.

Autoři: Zhu, Yuying Zhang, Shuning Li, Xiaoxiong a další

Zdroj: IEEE Sensors Journal; 9/15/2021, Vol. 21 Issue 18, p20685-20693, 9p

A New Unsupervised Online Early Fault Detection Framework of Rolling Bearings Based on Granular Feature Forecasting

Autoři: Keying Liu Wentao Mao Huadong Shi a další

Zdroj: IEEE Access, Vol 9, Pp 159684-159698 (2021)

Témata: 0209 industrial biotechnology, Early fault detection, denoising autoencoder, alarm threshold, 0202 electrical engineering, electronic engineering, information engineering, Electrical engineering. Electronics. Nuclear engineering, 02 engineering and technology, streaming data, anomaly detection, TK1-9971

Přístupová URL adresa: https://ieeexplore.ieee.org/ielx7/6287639/6514899/09634014.pdf
https://doaj.org/article/72ec87c5b0f040bb89ded97470ad752f

An ELM-based Deep SDAE Ensemble for Inter-Subject Cognitive Workload Estimation with Physiological Signals

Autoři: Zheng, Zhanpeng Yin, Zhong Zhang, Jianhua

Zdroj: Chinese Control Conference (CCC)
2020 39th Chinese Control Conference (CCC)

Témata: 0209 industrial biotechnology, Cognitive workloads, Ensemble learning, Stacked denoising autoencoders, 0202 electrical engineering, electronic engineering, information engineering, Extreme learning machines, 02 engineering and technology, Electroencephalograms

Popis souboru: application/pdf

Přístupová URL adresa: https://ieeexplore.ieee.org/document/9188806
https://oda.oslomet.no/oda-xmlui/handle/11250/2772135
https://hdl.handle.net/11250/2772135

A novel multimodal framework for automatic recognition of individual cattle based on hybrid features using sparse stacked denoising autoencoder and group sparse representation techniques.

Autoři: Kumar, Santosh Kumar, Sunil Shafi, Mehak a další

Zdroj: Multimedia Tools & Applications; Sep2022, Vol. 81 Issue 21, p31075-31106, 32p

Témata: ENDANGERED species, FEATURE extraction, FACE, EXTRACTION techniques

Health condition identification for rolling bearing using a multi-domain indicator-based optimized stacked denoising autoencoder.

Autoři: Yan, Xiaoan Liu, Ying Jia, Minping

Zdroj: Structural Health Monitoring; Sep2020, Vol. 19 Issue 5, p1602-1626, 25p

Témata: ROLLER bearings, DEEP learning, AUTOMATIC identification, LINEAR operators, MATHEMATICAL optimization, BIOLOGICALLY inspired computing, ALGORITHMS

Denoising Autoencoder for Iris Recognition in Noncooperative Environments.

Autoři: Luz, Eduardo Menotti, David

Zdroj: Progress in Pattern Recognition, Image Analysis, Computer Vision & Applications 20th Iberoamerican Congress, CIARP 2015, Montevideo, Uruguay, November 9-12, 2015, Proceedings; 2015, p200-207, 8p

Harnessing feature pruning with optimal deep learning based DDoS cyberattack detection on IoT environment.

Autoři: Yang, Eunmok Jeong, Sooyong Seo, Changho

Zdroj: Scientific Reports; 5/20/2025, Vol. 15 Issue 1, p1-15, 15p

Témata: CYBERTERRORISM, DENIAL of service attacks, OPTIMIZATION algorithms, ARTIFICIAL intelligence, FISH migration

A Novel Deep Learning Representation for Industrial Control System Data.

Autoři: Bowen Zhang Yanbo Shi Jianming Zhao a další

Zdroj: Intelligent Automation & Soft Computing; 2023, Vol. 36 Issue 3, p2703-2717, 15p

Témata: INDUSTRIAL controls manufacturing, CONVOLUTIONAL neural networks, DEEP learning, ARTIFICIAL intelligence, ANALOG integrated circuits, FEATURE extraction