Suchergebnisse - "Stacked Sparse autoencoder (SSAE)"

Myocardium Detection by Deep SSAE Feature and Within-Class Neighborhood Preserved Support Vector Classifier and Regressor

Autoren: Yanmin Niu Lan Qin Xuchu Wang

Quelle: Sensors, Vol 19, Iss 8, p 1766 (2019)

Schlagwörter: myocardium detection, cardiac magnetic resonance, region proposal, support vector classifier and regressor, stacked sparse autoencoder (SSAE), Chemical technology, TP1-1185

Relation: https://www.mdpi.com/1424-8220/19/8/1766; https://doaj.org/toc/1424-8220; https://doaj.org/article/514c027bf42f4be5a00fb438b3d7beee

Verfügbarkeit: https://doi.org/10.3390/s19081766
https://doaj.org/article/514c027bf42f4be5a00fb438b3d7beee

Analysis and Review of Extraordinary Machine Learning Approaches

Autoren: Tyagi, Nitin Gupta, Sandeep Pratap Srivastava, Arun et al.

Quelle: International Journal of Engineering and Technology; Vol. 7 No. 4.39 (2018): Special Issue 39; 915-920 ; 2227-524X ; 10.14419/ijet.v7i4.39

Schlagwörter: Random Recursive Support Vector Machine (R2SVM), Stacked Sparse autoencoder (SSAE), Stacked Denoising Autoencoder (SDAE), Convolutional Neural Network (CNN), Support Vector Machine (SVM)

Dateibeschreibung: application/pdf

Relation: http://www.sciencepubco.com/index.php/IJET/article/view/27728/14398; http://www.sciencepubco.com/index.php/IJET/article/view/27728

Verfügbarkeit: http://www.sciencepubco.com/index.php/IJET/article/view/27728
https://doi.org/10.14419/ijet.v7i4.39.27728

A denoising method for ECG signals based on CEEMDAN-TSO and stacked sparse autoencoders.

Autoren: Li S Li J Mao J et al.

Quelle: Computers in biology and medicine [Comput Biol Med] 2025 Apr; Vol. 188, pp. 109818. Date of Electronic Publication: 2025 Feb 20.

Publikationsart: Journal Article

Info zur Zeitschrift: Publisher: Elsevier Country of Publication: United States NLM ID: 1250250 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1879-0534 (Electronic) Linking ISSN: 00104825 NLM ISO Abbreviation: Comput Biol Med Subsets: MEDLINE

MeSH-Schlagworte: Electrocardiography*/methods , Algorithms* , Signal Processing, Computer-Assisted*, Humans ; Signal-To-Noise Ratio ; Autoencoder

Automatic Vertebrae Localization and Identification by Combining Deep SSAE Contextual Features and Structured Regression Forest.

Autoren: Wang X Zhai S Niu Y

Quelle: Journal of digital imaging [J Digit Imaging] 2019 Apr; Vol. 32 (2), pp. 336-348.

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

Info zur Zeitschrift: Publisher: Springer Country of Publication: United States NLM ID: 9100529 Publication Model: Print Cited Medium: Internet ISSN: 1618-727X (Electronic) Linking ISSN: 08971889 NLM ISO Abbreviation: J Digit Imaging Subsets: MEDLINE

MeSH-Schlagworte: Neural Networks, Computer* , Tomography, X-Ray Computed*, Pattern Recognition, Automated/*methods , Radiographic Image Interpretation, Computer-Assisted/*methods , Spine/*diagnostic imaging, Humans ; Spinal Diseases/diagnostic imaging