Figure 4.

Approaches for training pretrained models based on transfer learning. The weights of pretrained layers in the base models are modified during the learning process, whereas the frozen layers retain their weights (i.e., not modified). (a) A basic transfer learning approach, where the pretrained model is loaded and trained using the extracted features. (b–d) The proposed transfer learning approach, where three freezing techniques are applied and features from each model are concatenated to perform training.