Structured Summary
Abstract
Artificial neural networks designed to automatically learn features through the use of sequence of layers which transform one volume to the next. Convolutional neural networks initially produce a feature map by use of convolution layers consisting of a set of learnable filters convolved with input, i.e., having smaller widths and heights and the same depth as that of input volume.
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Synonyms
21 entry terms
- Convolutional Neural Network
- Neural Network, Convolutional
- AlexNet
- DenseNet
- Densely Connected Convolutional Networks
- EfficientNet
- GoogLeNet
- LeNet
- LeNet-5 Convolutional Neural Network
- MobileNets
- ResNets
- Residual Neural Network
- VGGNet
- Visual Geometry Group Network
- ZFNet
- GoogLeNets
- LeNet 5 Convolutional Neural Network
- Neural Network, Residual
- Residual Neural Networks
- VGGNets
- ZFNets
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Aspects Covered
9 allowable subheadings
Indexed with the subheadings classification, economics, ethics, history, legislation & jurisprudence, standards, statistics & numerical data, supply & distribution, trends.
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History Note
2025
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Previous Indexing
- Neural Networks, Computer (2005-2024)
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AMA Style
References
- National Library of Medicine. Convolutional Neural Networks. Medical Subject Headings (MeSH). 2026. Unique ID D000098415. http://id.nlm.nih.gov/mesh/2026/D000098415
- Convolutional Neural Networks. In: Wikipedia. https://en.wikipedia.org/wiki/Convolutional_neural_network
- Convolutional Neural Networks. In: Wikidata. https://www.wikidata.org/wiki/Q17084460