Suchergebnisse - sparse stacked denoising autoencoder*

An Anomaly Detection Method for Nonlinear Industrial Process Using Sparse Stacked Denoising Autoencoder

Autoren: Mingwei Yang YanHua Liu Hong Chen et al.

Quelle: 2023 9th International Conference on Systems and Informatics (ICSAI). :1-6

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

Autoren: Santosh Kumar Sunil Kumar Mehak Shafi et al.

Quelle: Multimedia Tools and Applications. 81:31075-31106

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

Network intrusion detection based on Contractive Sparse Stacked Denoising Autoencoder

Autoren: Yang Yang Li Wencui Meng Huiping et al.

Quelle: 2021 IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB). :1-6

A Nonnegativity-Constraint Sparse Stacked Denoising Autoencoder for Anomaly Detection in Electric Power Communication Network

Autoren: Zhuo Tao Yuanyuan Wang Yang Yang et al.

Quelle: 2020 IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB). :1-6

Schlagwörter: 9. Industry and infrastructure, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

A sparse stacked denoising autoencoder with optimized transfer learning applied to the fault diagnosis of rolling bearings

Autoren: Ping Liu Peng Fan Hui Wang et al.

Quelle: Measurement. 146:305-314

Schlagwörter: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Zugangs-URL: https://ui.adsabs.harvard.edu/abs/2019Meas..146..305S/abstract
https://www.sciencedirect.com/science/article/pii/S0263224119305950

Prediction of Recurrence using a Stacked Denoising Autoencoder and Multifaceted Feature Analysis of Pretreatment MRI in Patients with Nasopharyngeal Carcinoma.

Autoren: Liu Y Wang X Li J et al.

Quelle: Current radiopharmaceuticals [Curr Radiopharm] 2025; Vol. 18 (3), pp. 224-243.

Publikationsart: Journal Article

Info zur Zeitschrift: Publisher: Bentham Science Publishers Country of Publication: United Arab Emirates NLM ID: 101468718 Publication Model: Print Cited Medium: Internet ISSN: 1874-4729 (Electronic) Linking ISSN: 18744710 NLM ISO Abbreviation: Curr Radiopharm Subsets: MEDLINE

MeSH-Schlagworte: Nasopharyngeal Carcinoma*/diagnostic imaging , Nasopharyngeal Carcinoma*/radiotherapy , Nasopharyngeal Carcinoma*/pathology , Magnetic Resonance Imaging*/methods , Neoplasm Recurrence, Local*/diagnostic imaging , Nasopharyngeal Neoplasms*/diagnostic imaging , Nasopharyngeal Neoplasms*/radiotherapy , Nasopharyngeal Neoplasms*/pathology, Humans ; Female ; Male ; Middle Aged ; Adult ; Retrospective Studies ; Radiotherapy, Intensity-Modulated ; Aged ; Deep Learning ; Autoencoder

Classification of Thyroid Nodules with Stacked Denoising Sparse Autoencoder.

Autoren: Li Z Yang K Zhang L et al.

Quelle: International journal of endocrinology [Int J Endocrinol] 2020 Dec 07; Vol. 2020, pp. 9015713. Date of Electronic Publication: 2020 Dec 07 (Print Publication: 2020).

Publikationsart: Journal Article

Info zur Zeitschrift: Publisher: Wiley Country of Publication: Egypt NLM ID: 101516376 Publication Model: eCollection Cited Medium: Print ISSN: 1687-8337 (Print) Linking ISSN: 16878337 NLM ISO Abbreviation: Int J Endocrinol Subsets: PubMed not MEDLINE

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

Autoren: Kumar, Santosh Kumar, Sunil Shafi, Mehak et al.

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

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

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

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

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

Schlagwörter: Deep learning, Forecasting, Time series analysis

Firma/Körperschaft: Amazon Web Services Inc.

Robust Cell Detection and Segmentation in Histopathological Images Using Sparse Reconstruction and Stacked Denoising Autoencoders.

Autoren: Su H Xing F Kong X et al.

Quelle: Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention [Med Image Comput Comput Assist Interv] 2015 Oct; Vol. 9351, pp. 383-390. Date of Electronic Publication: 2015 Nov 18.

Publikationsart: Journal Article

Info zur Zeitschrift: Publisher: Springer Country of Publication: Germany NLM ID: 101249582 Publication Model: Print-Electronic Cited Medium: Print NLM ISO Abbreviation: Med Image Comput Comput Assist Interv Subsets: MEDLINE

MeSH-Schlagworte: Algorithms*, Brain Neoplasms/*pathology , Diagnosis, Computer-Assisted/*methods , Lung Neoplasms/*pathology, Cell Count ; Cell Shape ; Humans ; Image Processing, Computer-Assisted ; Machine Learning ; Reproducibility of Results ; Sensitivity and Specificity

Decoding whole-genome mutational signatures in 37 human pan-cancers by denoising sparse autoencoder neural network.

Autoren: Pei G Hu R Dai Y et al.

Quelle: Oncogene [Oncogene] 2020 Jul; Vol. 39 (27), pp. 5031-5041. Date of Electronic Publication: 2020 Jun 11.

Publikationsart: Journal Article; Research Support, N.I.H., Extramural; Research Support, Non-U.S. Gov't

Info zur Zeitschrift: Publisher: Nature Publishing Group Country of Publication: England NLM ID: 8711562 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1476-5594 (Electronic) Linking ISSN: 09509232 NLM ISO Abbreviation: Oncogene Subsets: MEDLINE

MeSH-Schlagworte: Deep Learning*, Genome, Human/*genetics , Neoplasms/*genetics, DNA/genetics ; Humans ; INDEL Mutation/genetics ; Point Mutation/genetics

Blind Denoising Autoencoder

Autoren: Majumdar, Angshul

Index Begriffe: Electrical Engineering and Systems Science - Signal Processing, Computer Science - Machine Learning, text

URL: http://arxiv.org/abs/1912.07358

Relational stacked denoising autoencoder for tag recommendation

Autoren: Wang, Hao Shi, Xingjian Yeung, Dit Yan

Index Begriffe: Conference paper

URL: http://repository.ust.hk/ir/Record/1783.1-72866
http://lbdiscover.ust.hk/uresolver?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rfr_id=info:sid/HKUST:SPI&rft.genre=article&rft.issn=&rft.volume=&rft.issue=&rft.date=2015&rft.spage=3052&rft.aulast=Wang&rft.aufirst=Hao&rft.atitle=Relational+stacked+denoising+autoencoder+for+tag+recommendation&rft.title=Proceedings+of+the+Twenty-Ninth+AAAI+Conference+on+Artificial+Intelligence%2C+Austin%2C+Texas%2C+USA
http://www.scopus.com/record/display.url?eid=2-s2.0-84958767160&origin=inward
http://gateway.isiknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=LinksAMR&SrcApp=PARTNER_APP&DestLinkType=FullRecord&DestApp=WOS&KeyUT=000485625503013
http://repository.ust.hk/ir/bitstream/1783.1-72866/1/621310-ConfP-17-fulltext-pre.pdf

Matrix factorization with denoising autoencoders for prediction of drug-target interactions.

Autoren: Sajadi SZ Zare Chahooki MA Tavakol M et al.

Quelle: Molecular diversity [Mol Divers] 2023 Jun; Vol. 27 (3), pp. 1333-1343. Date of Electronic Publication: 2022 Jul 23.

Publikationsart: Journal Article

Info zur Zeitschrift: Publisher: ESCOM Science Publishers Country of Publication: Netherlands NLM ID: 9516534 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1573-501X (Electronic) Linking ISSN: 13811991 NLM ISO Abbreviation: Mol Divers Subsets: MEDLINE

MeSH-Schlagworte: Algorithms* , Machine Learning*, Drug Interactions ; Research Design ; ROC Curve

Blind Denoising Autoencoder

Autoren: Angshul Majumdar

Quelle: IEEE Transactions on Neural Networks and Learning Systems. 30:312-317

Schlagwörter: Signal Processing (eess.SP), FOS: Computer and information sciences, Computer Science - Machine Learning, FOS: Electrical engineering, electronic engineering, information engineering, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology, Electrical Engineering and Systems Science - Signal Processing, Machine Learning (cs.LG)

Zugangs-URL: http://arxiv.org/pdf/1912.07358
https://pubmed.ncbi.nlm.nih.gov/29994276
http://arxiv.org/abs/1912.07358

Learning social representations with deep autoencoder for recommender system.

Autoren: Pan, Yiteng He, Fazhi Yu, Haiping

Quelle: World Wide Web. Jul2020, Vol. 23 Issue 4, p2259-2279. 21p.

Schlagwörter: *SOCIAL learning, *COLLECTIVE representation, *RECOMMENDER systems, *MATRIX decomposition, *SOCIAL influence, *SOCIAL interaction, *SOCIAL problems

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

Autoren: Roka, Sanjay Diwakar, Manoj

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

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

Research of stacked denoising sparse autoencoder.

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

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

Schlagwörter: *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.

Autoren: Lin, Da Wan, Qi

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

Schlagwörter: *ANTENNA radiation patterns, *PHASED array antennas, *SIGNAL denoising, *WIRELESS communications, *BANDWIDTHS

Face recognition via Deep Stacked Denoising Sparse Autoencoders (DSDSA).

Autoren: Görgel, Pelin Simsek, Ahmet

Quelle: Applied Mathematics & Computation. Aug2019, Vol. 355, p325-342. 18p.

Schlagwörter: *HUMAN facial recognition software, *OBJECT recognition (Computer vision), *IMAGE recognition (Computer vision), *IMAGE representation, *DEEP learning, *ARTIFICIAL neural networks