Fig. 1

The representative architectures of four models, including the TB-DROP. The upper-left panel is the model architecture of WDNN, which comprises two parts: wide part and deep part. The model architecture implemented in TB-DROP (upper-right) is a deep neural network (DNN). The bottom-left panel is the model architecture of DeepAMR, which comprises encoder, decoder, and output layers. The model architecture of CNNGWP in the bottom-right panel is a classic convolutional neural network which consists of a convolutional layer and a pooling layer