Inputs are 1st handed via some thoroughly connected layer, into a double-layer residual multihead notice as demonstrated in Fig. 7. Residual networks (Kaiming He, 2016), include feedforward to prevent neurons from going through exploding or vanishing gradients all through the learning approach. The absolutely connected layers from the residual bloc