Attention mechanisms, vision transformers, and the architectures replacing convolutions across vision tasks. We unpack how attention is used, misused, and reinvented in current research, from efficient attention branches to Mamba-style state space models.
Most deep learning systems for cancer grading are trained the same way an image classifier is trained to tell cats from dogs. Each tissue patch gets a single label, benign, well differentiated, moderately differentiated or poorly differentiated, and the network…
DIOR-VIT: Vision Transformers Learn the Order of Cancer Grades Read More »
Prostate cancer is, by the paper’s own framing, the second most frequently diagnosed cancer and the fifth leading cause of cancer death among men worldwide. Grading how aggressive a tumor looks under the microscope, a task pathologists perform using a…