Search Results - Stacked denoising sparse autoencoder*

Face recognition via Deep Stacked Denoising Sparse Autoencoders (DSDSA)

Authors: Görgel, Pelin Şimşek, Ahmet İstanbul University Cerrahpaşa Institutional Repository

Contributors: Görgel, Pelin Şimşek, Ahmet İstanbul University Cerrahpaşa Institutional Repository

Source: Applied Mathematics and Computation. 355:325-342

Subject Terms: Sparse autoencoders, 03 medical and health sciences, 0302 clinical medicine, 0202 electrical engineering, electronic engineering, information engineering, Deep learning, 02 engineering and technology, Face recognition

File Description: application/pdf

Access URL: https://ideas.repec.org/a/eee/apmaco/v355y2019icp325-342.html
https://doi.org/10.1016/j.amc.2019.02.071
http://www.sciencedirect.com/science/article/pii/S009630031930181X
https://dblp.uni-trier.de/db/journals/amc/amc355.html#GorgelS19
https://www.sciencedirect.com/science/article/abs/pii/S009630031930181X

Network Intrusion Detection Method Based on Stacked Denoising Sparse Autoencoder and Extreme Learning Machine

Authors: Guoling Zhang Jiaxing He Rui Li et al.

Source: 2020 2nd International Conference on Information Technology and Computer Application (ITCA). :194-199

Subject Terms: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Access URL: http://xplorestaging.ieee.org/ielx7/9421350/9421928/09421975.pdf?arnumber=9421975
http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=9421975

Classification of Thyroid Nodules with Stacked Denoising Sparse Autoencoder

Authors: Zexin Li Kaiji Yang Lili Zhang et al.

Source: Int J Endocrinol
International Journal of Endocrinology, Vol 2020 (2020)

Subject Terms: 03 medical and health sciences, 0302 clinical medicine, 13. Climate action, RC648-665, Diseases of the endocrine glands. Clinical endocrinology, Research Article, 3. Good health

File Description: text/xhtml

Access URL: https://downloads.hindawi.com/journals/ije/2020/9015713.pdf
https://pubmed.ncbi.nlm.nih.gov/33488708
https://doaj.org/article/85ee260c795a4cef89458a6f89338a3c
https://pubmed.ncbi.nlm.nih.gov/33488708/
https://downloads.hindawi.com/journals/ije/2020/9015713.pdf
http://downloads.hindawi.com/journals/ije/2020/9015713.pdf
https://europepmc.org/article/MED/33488708
https://www.hindawi.com/journals/ije/2020/9015713/
https://www.ncbi.nlm.nih.gov/pubmed/33488708

Stacked Denoising Sparse Autoencoder-Based Fuzzy Rule Classifiers

Authors: Rahul Kumar Sevakula Nishchal K. Verma

Source: Studies in Computational Intelligence ISBN: 9789811950728

Unsupervised Feature Learning With Distributed Stacked Denoising Sparse Autoencoder for Abnormal Behavior Detection Using Apache Spark

Authors: Naila Marir Huiqiang Wang Guangsheng Feng

Source: 2019 IEEE 2nd International Conference on Knowledge Innovation and Invention (ICKII). :473-476

Subject Terms: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Access URL: https://ieeexplore.ieee.org/document/9042645/
https://dblp.uni-trier.de/db/conf/ickii/ickii2019.html#MarirWF19
http://dblp.uni-trier.de/db/conf/ickii/ickii2019.html#MarirWF19

Radar Target Recognition Based on Stacked Denoising Sparse Autoencoder

Authors: Zhao Feixiang Liu Yongxiang Huo Kai

Source: Leida xuebao, Vol 6, Iss 2, Pp 149-156 (2017)

Subject Terms: Target recognition, Deep learning, Stacked denoising sparse autoencoder, Electricity and magnetism, QC501-766

File Description: electronic resource

Relation: http://radars.ie.ac.cn/CN/html/R16151.htm; https://doaj.org/toc/2095-283X

Access URL: https://doaj.org/article/1c2d823be05147f8a13145c2075c9645

Faulty elements diagnosis of phased array antennas using a generative adversarial learning-based stacked denoising sparse autoencoder

Authors: Da Lin Qi Wan

Source: Journal of Electromagnetic Waves and Applications. 33:382-407

Subject Terms: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Access URL: https://www.tandfonline.com/doi/full/10.1080/09205071.2018.1553689

A Stacked Denoising Sparse Autoencoder Based Fault Early Warning Method for Feedwater Heater Performance Degradation

Authors: Xingshuo Li Jinfu Liu Jiajia Li et al.

Source: Energies, Vol 13, Iss 22, p 6061 (2020)

Subject Terms: stacked denoising sparse autoencoder, feedwater heater, fault early warning, frequent pattern model, feature reduction, Technology

File Description: electronic resource

Relation: https://www.mdpi.com/1996-1073/13/22/6061; https://doaj.org/toc/1996-1073

Access URL: https://doaj.org/article/b7a25ca30337465a89c648d213539593

Research of stacked denoising sparse autoencoder

Authors: Jian Zhang Shifei Ding Nan Zhang et al.

Source: Neural Computing and Applications. 30:2083-2100

Subject Terms: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Access URL: https://link.springer.com/article/10.1007/s00521-016-2790-x
https://dblp.uni-trier.de/db/journals/nca/nca30.html#MengD0018

A novel modulation classification method in cognitive radios using higher-order cumulants and denoising stacked sparse autoencoder

Authors: Xu Zhu Takeo Fujii

Source: 2016 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA). :1-5

Subject Terms: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

M-ary Phase Position Shift Keying Demodulation Using Stacked Denoising Sparse Autoencoders

Authors: Conghui Lu Peng Chen Hua Zhong et al.

Source: Electronics; Volume 11; Issue 8; Pages: 1233

Subject Terms: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology, improved M-ary phase position shift keying (MPPSK), deep learning, autoencoders, demodulation

File Description: application/pdf

A modulation classification method in cognitive radios system using stacked denoising sparse autoencoder

Authors: Takeo Fujii Xu Zhu

Source: 2017 IEEE Radio and Wireless Symposium (RWS). :218-220

Subject Terms: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Access URL: http://ieeexplore.ieee.org/document/7885992/
https://doi.org/10.1109/RWS.2017.7885992
http://doi.org/10.1109/RWS.2017.7885992
https://dblp.uni-trier.de/db/conf/rws/rws2017.html#ZhuF17

On latent fingerprint minutiae extraction using stacked denoising sparse AutoEncoders

Authors: Richa Singh Prateekshit Pandey Anush Sankaran et al.

Source: IEEE International Joint Conference on Biometrics. :1-7

Subject Terms: 0211 other engineering and technologies, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology, 16. Peace & justice, 3. Good health

Access URL: https://ieeexplore.ieee.org/document/6996300/
https://dblp.uni-trier.de/db/conf/icb/ijcb2014.html#SankaranPVS14
http://www.iab-rubric.org/papers/Latent-SDAE.pdf
http://ieeexplore.ieee.org/document/6996300/

Static hand gesture recognition using stacked Denoising Sparse Autoencoders

Authors: Rahul Kala Gora Chand Nandi Varun Kumar

Source: 2014 Seventh International Conference on Contemporary Computing (IC3). :99-104

Subject Terms: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Access URL: https://dblp.uni-trier.de/db/conf/ic3/ic3-2014.html#KumarNK14
https://ieeexplore.ieee.org/document/6897155/

M-ary Phase Position Shift Keying Demodulation Using Stacked Denoising Sparse Autoencoders.

Authors: Lu, Conghui Chen, Peng Zhong, Hua et al.

Source: Electronics (2079-9292); Apr2022, Vol. 11 Issue 8, p1233-1233, 12p

Subject Terms: PHASE shift keying, DEMODULATION, PHASE detectors, RANDOM noise theory, IMAGE denoising

Multimodal cloud resources utilization forecasting using a Bidirectional Gated Recurrent Unit predictor based on a power efficient Stacked denoising Autoencoders

Authors: Hamzaoui Ikhlasse Duthil Benjamin Courboulay Vincent et al.

Source: Alexandria Engineering Journal, Vol 61, Iss 12, Pp 11565-11577 (2022)

Subject Terms: Multimodal instances prediction, Stacked Denoising Auto Encoders, Bidirectional Gated Recurrent Unit, Time series, Power efficiency, Engineering (General). Civil engineering (General), TA1-2040

File Description: electronic resource

Relation: http://www.sciencedirect.com/science/article/pii/S1110016822003295; https://doaj.org/toc/1110-0168

Access URL: https://doaj.org/article/d6a38b36e5104493bdf044e0bfa7d2ed

Research of stacked denoising sparse autoencoder.

Authors: Meng, Lingheng Ding, Shifei Zhang, Nan et al.

Source: Neural Computing & Applications; Oct2018, Vol. 30 Issue 7, p2083-2100, 18p

Subject Terms: SIGNAL denoising, ARTIFICIAL intelligence, MACHINE learning, DEEP learning, ENCODING

Faulty elements diagnosis of phased array antennas using a generative adversarial learning-based stacked denoising sparse autoencoder.

Authors: Lin, Da Wan, Qi

Source: Journal of Electromagnetic Waves & Applications; Feb2019, Vol. 33 Issue 3, p382-407, 26p, 4 Black and White Photographs, 7 Diagrams, 13 Graphs

Subject Terms: ANTENNA radiation patterns, PHASED array antennas, SIGNAL denoising, WIRELESS communications, BANDWIDTHS

Multimodal cloud resources utilization forecasting using a Bidirectional Gated Recurrent Unit predictor based on a power efficient Stacked denoising Autoencoders.

Authors: Ikhlasse, Hamzaoui Benjamin, Duthil Vincent, Courboulay et al.

Source: Alexandria Engineering Journal. Dec2022, Vol. 61 Issue 12, p11565-11577. 13p.

Subject Terms: Deep learning, Forecasting, Time series analysis

Company/Entity: Amazon Web Services Inc.

Deep Learning Approach Based on Tensor-Train for Sparse Signal Recovery

Authors: Cong Zou Fang Yang

Source: IEEE Access, Vol 7, Pp 34753-34761 (2019)

Subject Terms: Compressive sensing, deep learning, Tensor-Train, stacked denoising autoencoder, Electrical engineering. Electronics. Nuclear engineering, TK1-9971

File Description: electronic resource

Relation: https://ieeexplore.ieee.org/document/8663363/; https://doaj.org/toc/2169-3536

Access URL: https://doaj.org/article/7eb7a8bf675a46849f2b1b0a47dd7467