A Swin Transformer plus CNN decoder reports 0.9555 recall and 0.9849 accuracy on Kvasir-SEG, but lower F1 and precision than DUCK-Net, with claimed attention innovations absent from the architecture.
To- wards automatic polyp detection with a polyp appearance model
1 Pith paper cite this work. Polarity classification is still indexing.
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Hybrid(Transformer+CNN)-based Polyp Segmentation
A Swin Transformer plus CNN decoder reports 0.9555 recall and 0.9849 accuracy on Kvasir-SEG, but lower F1 and precision than DUCK-Net, with claimed attention innovations absent from the architecture.