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. 2022 Jun 22;4(1):20210072. doi: 10.1259/bjro.20210072

Figure 5.

Figure 5.

The VGG-16 architecture. The VGG16 consists of 13 convolutional layers, five max-pooling layers, and three fully connected layers. Consequently, the number of tunable parameters is 16 (13 convolutional layers and three fully connected layers).