Descriptor English: | Autoencoder |
Descriptor Spanish: | Autocodificador |
Descriptor Portuguese: | Autocodificador |
Descriptor French: | Without translation |
Entry term(s): |
Autoencoders |
Tree number(s): |
G17.035.250.500.250.250 G17.035.250.500.750.500 G17.035.297 G17.485.500.250 L01.224.050.375.530.250.250 L01.224.050.375.530.750.500 L01.224.050.375.605.500.250 L01.224.050.395 |
RDF Unique Identifier: | https://id.nlm.nih.gov/mesh/D000098446 |
Scope note: | An unsupervised learning technique where the machine learns patterns in unlabeled data sets, makes compressed representations and reconstructs the input as output at minimum loss of features from the input. Autoencoders are useful in denoising images, DIMENSIONALITY REDUCTION and feature extraction. |
Allowable Qualifiers: | No qualifiers |
Previous Indexing: |
Algorithms (2011-2024) Neural Networks, Computer (2011-2024) |
Public MeSH Note: | 2025 |
History Note: | 2025 |
DeCS ID: | 60835 |
Unique ID: | D000098446 |
Documents indexed in the Virtual Health Library (VHL): | Click here to access the VHL documents |
Date Established: | 2025/01/01 |
Date of Entry: | 2024/08/09 |
Revision Date: | 2023/12/06 |
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PHENOMENA AND PROCESSES
Mathematical Concepts [G17]Mathematical Concepts -
PHENOMENA AND PROCESSES
Mathematical Concepts [G17]Mathematical Concepts -
PHENOMENA AND PROCESSES
Mathematical Concepts [G17]Mathematical Concepts -
PHENOMENA AND PROCESSES
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INFORMATION SCIENCE
Information Science [L01]Information Science -
INFORMATION SCIENCE
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INFORMATION SCIENCE
Information Science [L01]Information Science -
INFORMATION SCIENCE
Information Science [L01]Information Science
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Autoencoder
- Preferred
Concept UI |
M000766685 |
Scope note | An unsupervised learning technique where the machine learns patterns in unlabeled data sets, makes compressed representations and reconstructs the input as output at minimum loss of features from the input. Autoencoders are useful in denoising images, DIMENSIONALITY REDUCTION and feature extraction. |
Preferred term | Autoencoder |
Entry term(s) |
Autoencoders |
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