Detailed architectures of branch net₁ , branch net₂, and SELayer adopted in this work, where FC is the fully connected layer and BN is the batch normalization layer. The input of branch net₁₍₂₎ experiences the initial feature extraction through a fully connected layer and then carries out the feature amplification by 4(2) SELayer. Trunk net is similar but it should be noted that there is an activation function before the output. SELayer in this work is a modified squeeze-and-excitation layer specially for fully connected architecture.