Application of deep learning-based convolutional neural networks in gastrointestinal disease endoscopic examination

Figure 4 VGGNet-16 architecture. VGGNet comprises 16 weight layers and is characterized by repeated use of small (3 × 3) convolution filters and a uniform layer design. This deep and consistent architecture enhances its ability to capture hierarchical features, and laid the foundation for deeper networks like ResNet.