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

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    Message definition (Convolutional Neural Networks)
    {| class="wikitable"
    |-
    ! 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
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