Deep Learning, Artificial Intelligence, Medical Imaging, Image Segmentation, Transformers.
normalized through Softmax. Dropout can be applied on A to avoid over-fitting. The final step of the block computes Y by: where Fold() is the reverse operation of Unfold() and CO is a hyper-parameter representing the dimension of the outputs. CK=CV=CO. For the global aggregation block,