Translations:Convolutional Neural Networks/22/en: Difference between revisions

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Message definition (Convolutional Neural Networks)

{| class="wikitable"
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! Architecture !! Year !! Key contribution !! Depth
|-
| '''LeNet-5''' || 1998 || Pioneered CNNs for handwritten digit recognition (MNIST) || 5 layers
|-
| '''AlexNet''' || 2012 || Won ImageNet; popularised ReLU, {{Term|dropout}}, GPU training || 8 layers
|-
| '''VGGNet''' || 2014 || Showed depth matters; used only <math>3 \times 3</math> filters throughout || 16–19 layers
|-
| '''GoogLeNet (Inception)''' || 2014 || Introduced inception modules with parallel filter sizes || 22 layers
|-
| '''ResNet''' || 2015 || Introduced residual connections enabling very deep networks || 50–152+ layers
|-
| '''DenseNet''' || 2017 || Connected each layer to every subsequent layer via dense blocks || 121–264 layers
|-
| '''EfficientNet''' || 2019 || Compound scaling of depth, width, and resolution || Variable
|}

Architecture	Year	Key contribution	Depth
LeNet-5	1998	Pioneered CNNs for handwritten digit recognition (MNIST)	5 layers
AlexNet	2012	Won ImageNet; popularised ReLU, dropout, GPU training	8 layers
VGGNet	2014	Showed depth matters; used only $3 \times 3$ filters throughout	16–19 layers
GoogLeNet (Inception)	2014	Introduced inception modules with parallel filter sizes	22 layers
ResNet	2015	Introduced residual connections enabling very deep networks	50–152+ layers
DenseNet	2017	Connected each layer to every subsequent layer via dense blocks	121–264 layers
EfficientNet	2019	Compound scaling of depth, width, and resolution	Variable