Regressor block: The regressor block consisted of multiple linear layers, a convolution layer, a BN layer, and a ReLu layer, as shown in Fig. 6d. A skip-connection architecture was adopted to retain the features and increase the ability of the block to represent non-linear relationships. The convolution block in the skip-connection structure was a convolution layer with multiple numbers of 1 × 1 convolution kernels. The number of the convolution kernels was the same as that of the output size of the second linear layer to ensure the consistency of the vector dimension. The input size and output size of each linear layer were adjustable to be applicable to actual cases.