VGG19卷积神经网络结构图

以下是VGG19卷积神经网络的结构图：

     Input
        |
 Convolution (64 filters, 3x3 kernel, same padding)
        |
        |
        Max Pooling (2x2 pool size)
        |
 Convolution (128 filters, 3x3 kernel, same padding)
        |
        |
        Max Pooling (2x2 pool size)
        |
 Convolution (256 filters, 3x3 kernel, same padding)
        |
 Convolution (256 filters, 3x3 kernel, same padding)
        |
        |
        Max Pooling (2x2 pool size)
        |
 Convolution (512 filters, 3x3 kernel, same padding)
        |
 Convolution (512 filters, 3x3 kernel, same padding)
        |
        |
        Max Pooling (2x2 pool size)
        |
 Convolution (512 filters, 3x3 kernel, same padding)
        |
 Convolution (512 filters, 3x3 kernel, same padding)
        |
        |
        Max Pooling (2x2 pool size)
        |
        Flatten
        |
        Dense (4096 units)
        |
        Dense (4096 units)
        |
        Dense (1000 units)
        |
     Output

注：卷积层的 filter 数量和 kernel 大小可能会因为不同的实现而有所不同。此处仅提供了一个通用的参考值。