Recognition of esophagitis in endoscopic images using transfer learning

Figure 1 Representation of model’s final architecture. In the proposed model, each image is used as an input for a deep neural network composed of four blocks of densely connected convolutional layers, together with convolutional and pooling transition layers. The network output is a binary classification.