Scheme of the general architecture of the LSBG ViT. The input image is split into small patches and flattened into a sequence of 1D vectors and combined with positional encoding. The numbered circular patches represent the position encoding, and the counterpart represents the flattened 1D sequence of the image patches. The combined 1D sequence is passed to the transformer layers. The extra learnable class embedding encodes the class of the input image after being updated by self-attention and passes it on to an MLP head to predict the output.